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This is just a quick reference on how to install pgadmin 3 if the autoinstall with yum command (sudo yum install pgadmin3) fails. Two routes would be available. Try running yum list pgadmin* ​If you see something like this: that means the package is available in the highlighted repository, you'd just need to add it. rpm -Uvh http://yum.postgresql.org/9.4/redhat/rhel-7-x86_64/pgdg-redhat94-9.4-3.noarch.rpm After that, try sudo yum install pgadmin3_94 (insert your actual version) 2. If you would like a different version (or the latest one) of pgadmin, what you could do is grab the .tar.gz file from here https://www.postgresql.org/ftp/pgadmin3/release/ Then manually install it. For example for version 1.22.2 (the version is just for demoing purposes – I grabbed the top one available in the list): mv pgadmin3-1.22.2.tar.gz /usr/local/src cd /usr/local/src tar –zxvf pgadmin3-1.22.2.tar.gz cd pgadmin3-1.22.2 ./configure make make install Then you would need to configure your server to allow remote user access of the database using pgadmin. Two config files would need to be modified: Open up the postgresql.conf configuration file.  Do a search or find for the phrase ‘listen_addresses’ without quotes.  In order to open the access up to all IP addresses change the value to a *.  The default is set to ‘localhost’ which does not allow connection from remote computers. Next open the pg_hba.conf configuration file. Scroll down to the bottom of the file to the section marked # IPv4 local connections.  Add in the following code on its own line, just underneath the 127.0.0.1/32 line necessary for ‘localhost’. host all all youripaddress/32          trust This will allow for local access of the database server to the computer with the IP address you specified.  To add additional remote computers simply add a new line with their appropriate IP address. Now that your configuration is complete restart the PostgreSQL database server for the changes to take effect. su – su postgres pg_ctl restart –D /usr/local/pgsql/data
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Not as simple a question as it sounds.  There more options than some might think and choosing the right one can be the difference between a well performing application and one that struggles as it scales up in size.  There are options both internal and external to the Thingworx platform that can be used.  Each has their own use cases and cost considerations.   Internal to Thingworx there are three options as the storage provider PostGreSQL, Microsoft SQL Server (Azure SQL for PTC hosted systems) and InFlux DB.  PostGreSQL can be used for storing the Thingworx model structure and data,  and is an open source technology, meaning no additional cost.  SQL Server allows the same model and data storage but has licensing costs associated.  Both perform well up to an estimated 500 Gb of data storage (this is a rough estimate dependant on use case).  For very high volume data InFlux is the choice, it performs well for large data sets.   External to Thingworx you can use virtually any data storage technology the provides a JDBC connector or even one that has a driver that can be used to create a Thingworx Extension via our SDK or edge SDKs.  The platform knows how to use JDBC drivers so this can easily be used to connect to relational data storage like Oracle.   The first real question to ask when making the choice of where to store data is, what does my data look like?  Many systems are adapted or migrated from legacy systems which may include relational data, others simply have this structure by necessity.  If the data will need to use complex SQL to retrieve (like using joins, like, cursors, temp tables, etc.) then store the data in a true relational database.  If it is simple historical data, time series data or data that does not require compounding or recursive calculation to be useful, then keep it in platform data storage.   The second question to ask is, how much data will I be storing.  This adds a bit of complexity to where data is best stored.  There is no limit to the number of records in any data structure however, the Thingworx Platform storage is optimized to store and retrieve time series data, using the ValueSteam and Stream types built into the Platform.  This is the most common IoT data structure and in this case you can refer back to the previous information when choosing  the correct backend storage.  Data tables can be used when contained in small data sets (around 100,000 records or less) you can use Platform storage for this as these are intended for largely static data structures.  Retrieving data when DataTables grow larger than this will begin to slow performance quickly. This is because currently Thingworx will do a full scan of the data, in this specific type of structure, when querying because all of the logic for the query or filter is done on the platform, not on the database (this will likely change in a future version).  So small amounts of data can be quickly loaded and parsed in memory. NOTE (Neo4j specific): In datatables if you add a index to a column, these indexes are used when calling "FindDataTableEntries" but not when using "QueryDataTableEntries".   Streams and ValueStreams, however, are optimized for time series data.  In these structures Thingworx has built in datetime filters that allow for very fast retrieval of data based on a date range.  When the number of records returned after the date range is applied is still a very large number (100,00 - 200,000) you may see a drop in performance of a query at that point.  Just as before, all records, after the date filter is applied, are returned to the Platform and further query and filtering are done in memory.   The querying/retrieval of data is commonly where the greatest performance issues are seen.  Using a JDBC connector to send the query to the database (even if it is PostGreSQL, SQL Server Or InFlux) can help, or if the historical data is not queried regularly you can move this data to a separate Thingworx data store (another DataTable or Stream).   That would leave only large data sets of non-time series data as the outlier.  This scenario could perform equally well (or poorly) primarily on how the data will be retrieved. If there are loose relationship between the data that need to be used then a relational system that would allow these to be executed on the database server is preferred.  Sequential data that does not need this type of processing could be stored in InFlux.   This is a base outline of considerations when designing data storage on your application.  Most use cases are unique and may have additional considerations around process and cost.
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  Quickly Build Mashup Widget Extensions and Extend Application Functionality with the Eclipse Plugin.   GUIDE CONCEPT   Extensions enable you to quickly and easily add new functionality to an IoT solution. Mashup widget extensions can be utilized to enhance a user's experience, your ability to develop robust applications, and make development easier as you move forward with your IoT development.   The Eclipse Plugin for ThingWorx Extension Development (Eclipse Plugin) is designed to streamline and enhance the creation of extensions for the ThingWorx Platform. The plugin makes it easier to develop and build extensions by automatically generating source files, annotations, and methods as well as updating the metadata file to ensure the extension can be imported.   These features allow you to focus on developing functionality in your extension, rather than spend unnecessary time getting the syntax and format of annotations and the metadata file correct.     YOU'LL LEARN HOW TO   Utilized the Eclipse Plugin and Extension SDK Create and configure an Extension project Create A mashup Widget Extension Build and import an Extension   NOTE: This guide's content aligns with ThingWorx 9.3. The estimated time to complete ALL parts of this guide is 60 minutes.     Step 1: Completed Example   Download the completed files for this tutorial: MashupWidgetSamples.zip. Download the Eclipse Plugin. Download Extensions SDK.   The MashupWidgetSamples.zip file provided to you contains a completed example of a simple Widget project and examples of more advanced widget source code. Utilize this file to see a finished example and return to it as a reference if you become stuck during this guide and need some extra help or clarification.   Keep in mind, this download uses the exact names for Entities used in this tutorial. If you would like to import this example and also create Entities on your own, change the names of the Entities you create.     Step 2: Create Mashup Widget Extension Project   First, let's get our tools installed and set. If you haven't created an extension before, see the Create An Extension guide on how to entirely configure your setup.   Download Eclipse ThingWorx SDK. Download Eclipse ThingWorx Plugin.   To create a new extensions project in the ThingWorx Extension Perspective, follow the steps below to get started:   Go to File->New->Project. Click ThingWorx->ThingWorx Extension Project.   Click Next. Enter the Project Name (for example, MyAwesomeExtension). Select Ant as your build framework. Gradle can be used if you are using a version of Eclipse that supports Gradle STS. Enter the SDK location by browsing to the directory where the Extension SDK zip is stored. Enter the Vendor information (for example, ThingWorx Labs). Change the default package version from 1.0.0 to support extension dependency. Click Next then click Finish. Your newly created project is added to the Package Explorer tab.   Creating Widgets   The ThingWorx Extensions SDK allows for easier development and in a shorter timeframe. The SDK provides steps for creating widgets, starting with an initial setup. Follow the steps below to get started on your own widget creation.   Choose the ThingWorx menu and select New Widget.   Select the parent project, in this case MyAwesomeExtension. Enter SimpleWidget for the name and A simple example of Widget creation. for description.   Click Finish.   A new folder under the /ui folder is created and contains the JavaScript and CSS files for the widget. The metadata.xml file under the configfiles directory is updated automatically. The generated JavaScript files contain a minimal implementation of the functions needed to produce a working widget.   Adding Third-Party JAR Files   There are scenarios in which a 3rd party JAR file might be required. None will be needed for this scenario, but take note of how to do it below.   Choose the Widget menu and select New Jar Resource. Select the parent project. Browse to and select the JAR file you want to add, and enter a description. Click Finish. The JAR file is added to the /lib folder and the metadata.xml file is updated automatically.   Adding Third-Party Resources and JavaScript Libraries   Third-party libraries, images, and other web artifacts needed for the widget should be placed in the /ui/<widgetname> folder or subfolders of that location. The *.ide.js and *.runtime.js files can then reference any of those artifacts via the relative path of: …/Common/extensions/<extensionname>/ui/<widgetname>/   For example, to include a third-party JavaScript library and CSS into your widget code, one would do the following: if (!jQuery().qtip) { $("body").append('<script type="text/javascript" src="../Common/extensions/MyAwesomeExtension/ui/SimpleWidget/include/qtip/jquery.qtip.js"></script>'); $("head").append('<link type="text/css" rel="stylesheet" href=" ../Common/extensions/MyAwesomeExtension/ui/SimpleWidget/include/qtip/jquery.qtip.css" />'); }     Step 3: Widget Lifecycle in the Mashup Builder   A widget has the following lifecycle stages within the Mashup Builder. During each lifecycle stage, the specified functions on the widget are called by the Mashup Builder.   Discovered   The widget is being loaded into index.html and added to the Widget toolbar/palette.   widgetProperties() - Called to get information about each widget (such as display name and description)   widgetEvents() - Called to get information about the events each widget exposes   widgetServices() - Called to get information about the services each widget exposes   Created   The widget is dragged onto a Mashup panel.   afterload() - Called after your object is loaded and properties have been restored from the file, but before your object has been rendered   Appended   The widget is appended to the workspace DOM element.   renderHtml() - Called to get an HTML fragment that will be inserted into the Mashup DOM element   afterRender() - Called after the HTML fragment representing the widget has been inserted into the Mashup DOM element and a usable element ID has been assigned to the DOM element holding the widget content. The DOM element is then ready to be manipulated.   Updated   The widget is resized or updated in the Widget property window.   beforeSetProperty() - Called before any property is updated   afterSetProperty() - Called after any property is updated   Destroyed   The widget is deleted from the mashup.   beforeDestroy() - Called right before the widget’s DOM element is removed and the widget is detached from its parent widget and deallocated. You should clean up resources (such as plugins and event handlers) acquired during the lifetime of the widget.     Step 4: Widget Coding Examples   The [widgetname].ide.js file must implement several functions to work correctly in the Mashup Builder using its API. Widgets can declare widget properties, services, and events in functions.   Mashup Builder Code   Below is sample code for a widget named SimpleWidget with a bindable string property named DisplayText. TW.IDE.Widgets.simplewidget = function () { this.widgetIconUrl = function() { return "../Common/extensions/MyAwesomeExtension/ui/simplewidget/SimpleWidget.ide.png"; }; this.widgetProperties = function () { return { name : "SimpleWidget", description : "A simple example of Widget creation.", category : ["Common"], properties : { DisplayText: { baseType: "STRING", defaultValue: "Hello, Awesome User!", isBindingTarget: true } } } }; this.renderHtml = function () { var mytext = this.getProperty('SimpleWidget Property'); var config = { text: mytext } var widgetTemplate = _.template( '<div class="widget-content widget-simplewidget">' + '<span class="DisplayText"><%- text %></span>' + '</div>' ); return widgetTemplate(config); }; this.afterSetProperty = function (name, value) { return true; }; };   Runtime Coding   To handle the widget at runtime, you need methods to do the following: Render the HTML at runtime Set up bindings after rendering the HTML Handle property updates Below is sample code of what the [widgetname].runtime.js may look like: TW.Runtime.Widgets.simplewidget = function () { var valueElem; this.renderHtml = function () { var mytext = this.getProperty('SimpleWidget Property'); var config = { text: mytext } var widgetTemplate = _.template( '<div class="widget-content widget-simplewidget">' + '<span class="DisplayText"><%- text %></span>' + '</div>' ); return widgetTemplate(config); }; this.afterRender = function () { valueElem = this.jqElement.find(".DisplayText"); valueElem.text(this.getProperty("DisplayText")); }; this.updateProperty = function (updatePropertyInfo) { if (updatePropertyInfo.TargetProperty === "DisplayText") { valueElem.text(updatePropertyInfo.SinglePropertyValue); this.setProperty("DisplayText", updatePropertyInfo.SinglePropertyValue); } }; };   Advanced Examples   If you have a local installation of the ThingWorx Composer, you can find examples of widgets in the Tomcat_Installation_Folder/webapps/Thingworx/Common/thingworx/widgets directory. DO NOT EDIT THESE FILES!. You will be able to mimic widgets you like to use them as a basis for new widgets. Or, just take notes on these items which will be covered more in-depth later in this guide.   Additional Features   You can incorporate the following features into your widgets: Services that can be bound to events (such as Click of a Button, Selected Rows Changed, or Service Completed) Events that can be bound to various services (for example, invoke a service and navigate to a mashup) Properties that can be bound out You can access the full power of JavaScript and HTML in your widget code at runtime. Anything that can be accomplished using HTML and JavaScript is available in your widget.     Click here to view Part 2 of this guide.  
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Setting up the ThingWorx Server RemoteThing, ApplicationKey, and TunnelSubsystem Tunneling from the ThingWorx platform to an Edge Device can be easily done with a few preparation steps on the platform side: Create an ApplicationKey entity on the ThingWorx server so that the EMS or SDK you are using can authenticate with the platform Create a RemoteThingWithTunnels or RemoteThingWithTunnelsAndFileTransfer Thing for the remote device to bind to Either ThingTemplate will work, the only difference is if you want to use any native file transfer capabilities that are provided by ThingWorx In the newly created Thing, on the General Information page, click on the drop-down menu next to Enable Tunneling and select Override - Enabled ​Go to the Configuration​ section under ​Entity Information ​on the right and click on the Add My Tunnel ​button The Tunnel Name is used to identify what tunnel to use in the RemoteAccessWidget you will bind to the tunnel The Host will remain 127.0.0.1 because this is from the perspective of where the vnc server is to the remote device In my example they are on the same device The Port value should be the Port that the server is listening on This is typically 5900, but my vnc server is running on port 5901 for this example The App URI can be cleared out because we do not need to reference that file Here is a link to a further explanation on what the App URI is for: ThingWorx Tunneling App URI's The # of Connections and Protocol can remain their default values unless you have a reason to change them Navigate back to Home and look for the TunnelSubsystem under the Subsystems page Click on the TunnelSubsystem Click on the Configuration option on the left Modify the Public host name used for tunnels field and the Public port used for tunnels field to the host and port of your ThingWorx server Save and close the TunnelSubsystem Configuring the Edge Device For this example I'm going to keep it simple and set up an EMS (Edge MicroServer) instead of an SDK. This EMS will be on a totally separate device (an Ubuntu machine), while my ThingWorx server is on my local machine. Download the latest EMS onto a separate machine Configure the config.json file settings to match the server's host, port, and application key The ​tunnel​ block will be necessary to add as well, see below for an example of a working config.json file: Configure the config.lua file to match the name of the RemoteThingWithTunnels we created earlier; in this instance the name of my RemoteThing is ​EdgeThing​: Run the EMS and LSR (Lua Script Resource) The LSR EdgeThing​ will bind automatically to the RemoteThingWithTunnels we created earlier To verify there is successful connection between the platform and EMS go to the ​EdgeThing​'s Properties page and check to see if the ​isConnected ​property is currently set to ​true​ If it's not, please refer to this Help Center section for further troubleshooting. There is a list of error codes here. Installing a VNC Viewer and Server The next series of steps talks about configuring a VNC Server on the EMS machine and a VNC Client on the computer you are using to connect to the server. For this example I will be using packages tightvncserver, xfce4, xfce4-goodies, and vnc4server on my Ubuntu machine that hosts the EMS, and I will be using the tightvnc viewer available for download here. The following steps describe how to configure the Ubuntu machine so that it will be ready to accept vnc requests: I want to note that I am specifically using a 64-bit Ubuntu 14.04 LTS OS Run the following commands: sudo apt-get update sudo apt-get install xfce4 xfce4-goodies tightvncserver Run the vncserver and you will be prompted to setup a password I used password to keep it simple, but you will want to use something relatively secure We will want to kill this instance right away so we can proceed with further configuration vncserver -kill :1 ​Make a backup of the ​xstartup​ file in case things go awry mv ~/.vnc/xstartup ~/.vnc/xstartup.bak Create a new xstartup ​file to proceed with the setup nano ~/.vnc/xstartup Insert the following commands into the file, and they will be exercised every time the server starts or is restarted: #!/bin/bash xrdb $HOME/.Xresources startxfce4 & The first command in the file tells the VNC's GUI framework to reference the .Xresources file, which is where a user can change vnc settings The second command launches the XFCE -- the graphical software Ensure that the xstartup ​file has executable privileges: sudo chmod +x ~/.vnc/xstartup Start the server back up with vncserver For the machine that is being used to view the Mashup, install the tightvnc server from the link mentioned above. You should double-click the tightvnc-jviewer.jar file to run the viewer application now so it is up and ready for the ​Establishing a Tunnel ​section​. Creating the RemoteAccess Mashup This next portion of the tutorial covers creating the Mashup that will be asked by any user who wants to remote into the Edge device. Go to Composer Home and open the Mashup menu option on the left side of the screen Add a new Static or Dynamic Mashup Drag-and-drop a RemoteAccessWidget onto the Mashup Click on the RemoteAccessWidget and modify the RemoteThingName, TunnelName, and AcceptSelfSignedCertificates ​properties for the connection The RemoteThingName is the name of the Edge Thing the remote device is bound to The TunnelName is the name of the tunnel we added to the Edge Thing in the Configuration screen The AcceptSelfSignedCertificates is only used when using an SSL connection with self signed certs View the Mashup and the RemoteAccess Widget should have a green plus sign on it if the connection from the EMS to platform is up and connected Establishing a Tunnel The following section is the last part of the process where we actually establish a tunnel between the client, platform, and remote device. Open the Mashup with the RemoteAccess Widget if you closed it Click on the RemoteAccess Widget to being the wsadapter.jnlp download Once that has completed click on the wsadapter.jnlp file to run it Keep in mind that there is a default 90 second timeout defined in the TunnelSubsystem that will render the wsadapter.jnlp file useless and you will have to download a new one if the connection is not established within that timeframe If you receive the following error message you may need to reconfigure your TunnelSubsystem configuration options for your server because the thingworx-tunnel-launcher.jar was unable to be found at that address If you receive the following error message after you will need to modify your security settings in your Java options. This is done by opening ​Configure Java​, navigating to the ​Security ​tab, and then adding your ThingWorx server's IP and port to the site list via the ​Edit Site List...​ button You should have received a Security Warning message upon successfully finding the thingworx-tunnel-launcher.jar file that you will click the ​Run​ button on and check the I accept the risk and want to run this application​ A pop-up, like the following, will be seen and you know the tunnel is now open for tightvnc to connect through Do not click ​OK​, instead, please proceed to the next step. Clicking OK will close the tunnel if you have not connected to the EMS via the VNC Viewer yet. Open the tightvnc-jviewer.jar and type in the corresponding host and port that a vnc connection should be established to: localhost ​ and port ​16345​ are used because we have already established a connection to the EMS and it is listening for a vnc connection on port 16345 -- per the ThingWorx pop-up we just saw Click ​Connect​ and a new window should appear showing the GUI environment of your Ubuntu server like below
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  Question: What should I know about using ThingWorx with InfluxDB to store my time series data? Hi, ThingWorx users!   It’s here! Thanks for waiting patiently since my previous post announcing ThingWorx’ new support of InfluxDB as a time series persistence provider.   As of our 8.4 release, you can now use InfluxDB to store your ThingWorx time series data with incredible power and ease.   Want to learn more? Check out the following FAQs:   1. What is InfluxDB? Who is InfluxData? InfluxDB is a time series database designed to handle high write and query loads. It is meant to be used as a backing store for any use case involving large amounts of timestamped data, like monitoring, application metrics, IoT sensor data, and real-time analytics that you’d find in ThingWorx.   InfluxDB is created by InfluxData, an awesome company that we are proud to call a PTC partner.   2. When would I want to use InfluxDB for IIoT? While the ThingWorx IIoT platform supports multiple databases to persist IIoT data and is agnostic when it comes to the storage layer, InfluxDB is the ideal choice for time series. When the number of connected devices increases, along with the amount of streaming data, the need to have a high-scale telemetry database choice is obvious.   For very high scale data ingestion, InfluxDB should be used as a persistent provider with the ThingWorx platform for multiple reasons. Its flexibility and ease of use provides native support for standard time series functions, including: sampling, interpolation, time bucketing, aggregation, selector, transformation, predictor, etc. It does all of this while supporting a high compression of data (~45x) with the ability to handle thousands of writes per second and read thousands of rows in milliseconds.   Check out this article by our Enterprise Deployment Center (EDC) explaining why InfluxDB is great for small ThingWorx applications.   3. What are the three different flavors of InfluxDB? InfluxDB Open Source (TICK Stack), InfluxDB Enterprise & InfluxDB Cloud. Here’s more info on each: InfluxDB Open Source (TICK Stack): This is the open-source version of the product available to download via the InfluxData website. Also included here are the other projects that comprise the TICK Stack, including: [T] Telegraf; open source collection agent [I] InfluxDB; open source time series database [C] Chronograf; open source visualization application [K] Kapacitor; open source streaming processing engine; side car to InfluxDB InfluxDB Enterprise: This is the commercial software version of InfluxDB for high availability clustering and the recommended time series database to be used for production with ThingWorx 8.4 and later. InfluxDB Enterprise works with the rest of the TICK stack interchangeably (Telegraf, Chronograf, Kapacitor). InfluxDB Cloud: This is the commercial service version of InfluxDB, hosted on AWS, managed by InfluxData, and delivered as a service to customers. InfluxDB Cloud works with the rest of the TICK stack interchangeably (Telegraf, Chronograf, Kapacitor). To learn more about the different modules of InfluxDB (Telegraf, Chronograf, Kapcitor), check out InfluxData Introduction for documentation or InfluxData Products for product info.   4. What is the difference between InfluxDB opensource and enterprise? InfluxDB Open Source is available in a single (1 only) data node configuration only, albeit with “n” number of vCPU or “cores” provisioned on that single node.  InfluxDB Enterprise is available in multiple (2 or more) data node configuration, also with “n” number of vCPU or “cores” provisioned to each node. The Enterprise edition is generally preferred for production deployments that require high availability, replication, and redundancy. Provisioned along with the data nodes are three (3) meta nodes and a load balancer to distribute data workload across the multiple nodes. Typical configurations are in even increments of data nodes (i.e. 2, 4, 6, 8, etc.).   5. Where can I find the pricing overview for buying enterprise licenses for InfluxDB? The PTC product and go-to-market team have defined commercial pricing for InfluxDB Enterprise. For help with pricing, reach out to Chris Wensley (cwensley@ptc.com) and Anders Hinrichsen (anders@influxdata.com).   6. How do I configure InfluxDB with ThingWorx? We’ve outlined the steps for you in the ThingWorx Help Center and created a quick video to instruct you on how to install InfluxDB with ThingWorx. (view in My Videos) To see the current version of InfluxDB that we support, read our ThingWorx 9.0 System Requirements guide.   7. How do I configure InfluxDB and ThingWorx in a high availability scenario? With the ability to leverage multiple data stores, we work to provide the flexibility to best meet the needs of your IT preferences and investments. InfluxDB helps us do that. To configure ThingWorx for High Availability, please refer to this section of the ThingWorx Platform 9 Help Center. To configure InfluxDB for High Availability at the database level, please refer to InfluxData’s documentation on how to Install and deploy InfluxDB Enterprise clusters.   8. Where can I learn more about how to monitor and manage InfluxDB? Monitoring info for InfluxDB can be found here: Monitoring Tools for TICK Stack.   9. How can I tune and optimize InfluxDB with ThingWorx? The best approach for running InfluxDB with PTC ThingWorx 8.4 (or later) is to treat the workload and configuration just as you would in a stand-alone deployment. We suggest to stick to the recommendations in the InfluxDB and TICK stack documentation.   10. How do I perform backup and recovery of ThingWorx with InfluxDB? Please see the ThingWorx Platform Backup and Recovery Planning Technical Brief to plan for back and recovery. You can also find more more details on taking backups and restoring data from InfluxDB in the Backing up and restoring in InfluxDB Enterprise overview.   11. Where can I learn more about sampling, interpolation, time bucketing, aggregation, pivot​ and other key features of InfluxDB? Features of InfluxDB can be found here: InfluxData Time Series Platform. Implementation of InfluxDB features can be found here: Getting Started with InfluxDB.   12. What are all the different persistence providers supported with ThingWorx? When should I use InfluxDB? ThingWorx supports the following model and data provider storage options: H2, PostgreSQL, MS SQL Server and AzureSQL ThingWorx supports the following data provider only storage options: InfluxDB Please refer to the model and data best practices section of the ThingWorx 9 Help Center for further information on options how to store your model and data with ThingWorx.   We have also updated the ThingWorx Platform 9.0 Sizing Guide to provide relevant information to estimate the amount of processing and memory that ThingWorx may need to meet your requirements. It also provides guidance on when to use InfluxDB for your scale needs.   13. When should I use InfluxDB over DataStax Enterprise (DSE)? Here is a good blog post that benchmarks time series data performance of InfluxDB vs. Cassandra, which is the core of DataStax Enterprise (DSE). In specific use cases, InfluxData Enterprise may be more cost effective when compared to similar telemetry use cases with DSE.   14. How can I migrate my data from PostgreSQL to InfluxDB? Migration from PostgreSQL or MSSQL is supported by the ThingWorx in-built data tools, which can export entities and data from PostgreSQL or MSSQL and then import them into InfluxDB.   Details on how to upgrade to ThingWorx 9.0 can be found in the Upgrading ThingWorx  section of the ThingWorx 9 Help Center.   15. Should I use InfluxDB as a time series store rather than OSI PI, IP21, or others? For ThingWorx 8.4 and later, InfluxDB is the recommended time series store. This can be implemented at the edge with ThingWorx (i.e. “front end”) using the open source edition and can also be implemented at the hub (i.e. “back end”) using either of the commercial editions designed for HA production workloads.   As always, ThingWorx can connect to most industrial software, including OSI PI, IP21, etc. with our integration toolset.   That’s a wrap—almost! We’ve added two extra questions for you.   16. What’s on the roadmap for ThingWorx with InfluxDB? Key development work to fully leverage built-in InfluxDB querying capabilities and support InfluxDB 2.0 in future ThingWorx releases Leveraging query operations capabilities from InfluxDB to further improve query performance Supporting additional native InfluxDB features (e.g. continuous queries)   17. What should I do if I need technical support with InfluxDB? If you select InfluxDB as your persistence provider, then all support requests related to configuring InfluxDB can be logged through PTC Technical Support at https://support.ptc.com or by calling 1-800-477-6435. You may also want to use the PTC Community to learn and collaborate with the growing PTC developer community. For all other requests related to database management, troubleshooting, monitoring, and administration, we encourage you to reach out to InfluxData directly based on your enterprise purchase contract made with InfluxData. PTC customers using InfluxDB can also email ptc-support@influxdata.com for support requests related to InfluxData.   If you’re as excited as I am about the ability to store your time series data with InfluxDB, let me know in the comments below!   Until next time, if you have any questions, just ask Kaya!
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Overview The Axeda Platform is a secure and scalable foundation to build and deploy enterprise-grade applications for connected products, both wired and wireless. This article provides you with a detailed feature overview and helpful links to more in-depth articles and tutorials for a deeper dive into key areas. Types of Connected Product Applications M2M applications can span many vertical markets and industries. Virtually every aspect of business and personal life is being transformed by ubiquitous connectivity. Some examples of M2M applications include: Vehicle Telematics and Fleet Management - Monitor and track the location, movements, status, and behavior of a vehicle or fleet of vehicles Home Energy Monitoring - Smart energy sensors and plugs providing homeowners with remote control and cost-saving suggestions Smart Television and Entertainment Delivery - Integrated set-top box providing in-view interaction with other devices – review your voicemails while watching a movie, chat with your Facebook friends, etc. Family Location Awareness - Set geofences on teenagers, apply curfews, locate family members in real time, with vehicle speed and condition Supply Chain Optimization - Combine status at key inspection points with logistics and present distribution managers with an interactive, real-time control panel Telemedicine - Self-monitoring/testing, telecardiology, teleradiology Why Use a Platform? Have you ever built a Web application? If so, you probably didn't create the Web server as part of your project. Web servers or Web application servers like Apache HTTPd or JBoss manage TCP sockets, threads, the HTTP protocol, the compilation of scripts, and include thousands of other base services. By leveraging the work done by the dedicated individuals who produced those core services, you were able to rapidly build an application that provided value to your users.  The Axeda Platform is analogous to a Web server or a Web application server, but provides services and a design paradigm that makes connected product development streamlined and efficient. Anatomy of an Axeda Connected Product Connected Products can really be anything that your product and imagination can offer, but it is helpful to take pause for some common considerations that apply to most, if not all of these types of solutions. Getting Connected - Bring your product or equipment to the network so that it can provide information to the solution, and react to commands and configuration changes orchestrated by the application logic. Manage and Orchestrate - Script your business logic in the cloud to tie together remote information with information from other business systems or cloud-based services, react to real-time conditions, and facilitate batch operations to synchronize, analyze, and integrate. Present and Report - Build your user experiences, enabling people to interact with your connected product, manage workflows around business processes, or facilitate data analysis. Let's take a look at the Axeda Platform services that help with each of these solution considerations. Getting Connected Wired & Wireless Getting connected can assume all sorts of shapes, depending on the environment of your product and the economics of your solution. The Axeda Platform makes no assumption about connectivity, but instead provides features and functionality to help you connect.For wireless applications, especially those which may use cellular or satellite communications, the speed and cost of communication will be an important factor.  For this reason, Axeda has created the Adaptive Machine Messaging Protocol (AMMP), a cross-platform, efficient HTTP-based protocol that you can use to communicate bi-directionally with the platform.  The protocol is expressive, robust, secure, and most importantly, able to be implemented on a wide range of hardware and programming environments. When you are faced with connecting legacy products that may be communicating with a proprietary messaging protocol, the Axeda Platform can be extended with Codecs to "learn" your protocol by translating your device's communication format into a form that the platform can understand. This is a great option for retrofitting existing, deployed products to get connectivity and value today, while designing your next-generation of product with AMMP support built-in. Manage and Orchestrate The Data Model defines the information and its behavior in the Axeda Platform. Rules Rules form the heart of a dynamic connected application. There are three types of rules that can be leveraged for your orchestration layer: Expression rules run in the cloud, and are configured and associated with your assets through the Axeda Admin UI or SDK. These rules have an If-Then-Else structure that's easy to create and understand. They're like a formula in a spreadsheet. For example, say your asset has a dataitem reading for temperature: [TODO: Image of dataitem TEMP] This rule compares the temperature to 80 every time a reading is received. When this happens, the rule creates an alarm with name "High Temp" and severity 100.Learn more about Expression Rules. State Machines help organize Expression Rules into manageable groups that apply to assets when the assets are in a certain state. For example, if your asset were a refrigerated truck, and you were interested in receiveing an alert when the temperature within the cargo area rose above a preset threshold, you would not want this rule to be applied when your truck asset is empty and parked in the distribution center lot. In this case, you might organize your rules into a state machine called “TruckStatus”. The TruckStatus state machine would then consist of a set of states that you define, and the rules that execute when the truck is in a particular state. [TODO - show state machine image?] State “Parked”: IF doorOpen THEN … State “In Transit”: IF temperature > 40 THEN… State “Maintenance”: <no rules> You can learn more about state machines in an upcoming technical article soon. Scripting Using Axeda Custom Objects, you can harness the power of the Axeda SDK to gain access to the complete set of platform data and functionality, all within a script that you customize. Custom Object scripts can be invoked in an Expression Rule to provide customized and flexible business logic for your application. Custom Object scripts are written in a powerful scripting language called Groovy, which is 100% Java syntax compatible. Groovy also offers very modern, concise syntax options that make your code simple and easy to understand. Groovy can also implement the body of a web service method. We call this Scripto. Scripto allows you to write code and call that code by name through a REST web service. This allows a client application to call a set of customized web services that return exactly the information and format needed by the application. Here is a beginning tutorial on Scripto.  This site includes many Scripto examples called by different Rich Internet Applications (RIA). Location-Based Services Knowing where something is, and where it has been, opens a world of possible application features. The Axeda Platform can keep track of an asset’s current and historical location, which allows your applications to plot the current position of your assets on a map, or show a breadcrumb trail of where a particular asset has been. Geofences are virtual perimeters around geographic locations. You can define a geofence around a physical location by describing a center point and radius, or by “drawing” a polygon around an arbitrary shape. For instance, you may have a geofence around the Boston metro that is defined as the center of town with a 10-mile radius. You may then compare an asset’s location to this geofence in a rule and trigger events to occur. IF InNamedGeofence(“Boston”) THEN CreateAlarm(…) You can learn more about geofences and other location-oriented rule features in an upcoming tutorial. Integration Queue In today’s software landscape, almost no complete solution is an island unto itself. Business systems need to interoperate by sharing data and events, so that specialized systems can do their job without tight coupling. Messaging is a robust and capable pattern for bridging the gap between systems, especially those that are hosted in the cloud. The Axeda Platform provides a message queue that can be subscribed to by external systems to trigger processes and workflows in those systems, based on events that are being tracked within the platform. A simple ExpressionRule can react to a condition by placing a message in the integration queue as follows: IF Alarm.severity > 100 THEN PublishObject() A message is then placed in the queue describing the platform event, and another business system may subscribe to these messages and react accordingly. Web Services Web Services are at the heart of a cloud-based API stack, and the Axeda Platform provides full comprehensiveness or flexibility. The platform exposes Web Service operations for all platform data and configuration meta data. As a result, you can determine the status of an asset, query historical data for assets, search for assets based on their current location, or even configure expression rules and other configuration settings all through a modern Web Service API, using standard SOAP and REST communication protocols. Scripto Web Service APIs simplify system integration in a loosely-coupled, secure way, and we have a commitment to offering a comprehensive collection of standard APIs into the Axeda Platform. But we can't have an API that suits every need exactly. You may want data in a particular format, such as CSV, JSON, or XML. Or some logic should be applied and its inefficient to query lots of data to look for the bit you want. Wouldn’t you rather make the service on the other side do exactly what you want, and give it to you in exactly the format you need? That is Scripto – the bridge between the power and efficiency of the Axeda Custom Object scripting engine, and a Web Service client. Using Scripto, you can code a script in the Groovy language, using the Axeda SDK and potentially mashing up results from other systems, all within the platform, and expose your script to an external consumer via a single, REST-based Web Service operation. You create your own set of Web Services that do exactly what you want. This powerful combination let’s you simplify your Web Service client code, and give you easy access and maintainability to the scripted logic. Present Rich Internet Applications are a great way to build engaging, information-rich user experiences. By exposing platform data and functions via Web Services and Scripto, you can use your tool of choice for developing your front-end. In fact, if you choose a technology that doesn’t require a server-side rendering engine, such as HTML + AJAX, Adobe Flash, or Microsoft Silverlight, then you can upload your application UI files to the Axeda Platform and let the platform serve your URL! Addition references for using RIAs on the Axeda Platform: Axeda Sample Application: Populating A Web Page with Data Items Extending the Axeda Platform UI - Custom Tabs and Modules Far-Front-Ends and Other Systems If a client-only user RIA interface is not an option for you, you can still use Web Services to integrate platform information into other server-side presentation technologies, such as Microsoft Sharepoint portal or a Java EE Web Application. You can also get lightning-fast updates for your users with the Axeda Machine Streams that uses ActiveMQ JMS technology to stream data in real-time from the Axeda Platform to your custom data warehouses.  While your users are viewing a drill down on a set of assets, they can receive asynchronous notifications about real-time data changes, without the need to constantly poll Web Services. Summary Building Connected Products and applications for them is incredibly rewarding job. Axeda provides a set of core services and a framework for bringing your application to market.
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Want to do a REST call from ThingWorx Want to use REST to send request to External System. Want to get data from other system using REST Here is how you can do this.... ThingWorx has ContentLoaderFunctions API which provides services to load or post content to and from other web applications. One can issue an HTTP request using any of the allowed actions (GET, POST, PUT, DELETE). List of available ContentLoaderFunctions: Delete GetCookies GetJSON GetText GetXML LoadBinary LoadImage LoadJSON LoadMediaEntity LoadText LoadXML PostBinary PostImage PostJSON PostMultipart PostText PostXML PutBinary PutJSON PutText PutXML Example: Using LoadXML snippet in a custom service to retrieve an XML document from a specific URL Insert the LoadXML snippet into a custom service var params = {     proxyScheme: undefined /* STRING */,     headers: "{ 'header1':'value1','header2':'value2'}" /* JSON */,     ignoreSSLErrors: false /* BOOLEAN */,     useProxy: undefined /* BOOLEAN */,     proxyHost: undefined /* STRING */,       url: "http://some_url/sampleXMLDocument.xml" /* STRING */,     timeout: 30000 /* NUMBER */,     proxyPort: undefined /* INTEGER */,     password: "fakePassword" /* STRING */,     username: "Administrator"/* STRING */ }; var result = Resources["ContentLoaderFunctions"].LoadXML(params); The snippet above contains an example of how to format any headers in JSON that need to be passed in, the URL that points directly to some XML document, a password, username, timeout, and ignoreSSLErrors set to false When LoadXML is exercised it will retrieve the XML document, and this can then be parsed or handled however is necessary To see the XML document that is returned from this service the service can be called from a third-party client, such as Postman Note: If a proxy or username and password are required to connect to the URL, those parameter MUST be specified Using the PostXML snippet in a custom service to send content to another URL, in this example, another service in Composer Insert the PostXML snippet into a custom service var content = "<xml><tag1>NAME</tag1><tag2>AGE</tag2></xml>"; var params = {  url: "http://localhost/Thingworx/Things/thingName/Services/serviceName?postParameter=parameterName" /* STRING */, content: content /* STRING */, password: "admin" /* STRING */, username: "Administrator" /* STRING */ }; var result = Resources["ContentLoaderFunctions"].PostXML(params); When posting XML content to another ThingWorx service the postParameter header must be defined in the url parameter for the PostXML snippet  The postParameter header, in the url parameter, is set equal to the name of the input parameter for the service we are POSTing to Change the parameterName variable in the url to the name of the input parameter defined for the service The content parameter is set to the XML content that will be passed into the function or manually specified Note: When declaring namespace URLs in an element make sure that there is a white space in between each declaration ex: <root xmlns:h="http://www.w3.org/TR/html4/" xmlns:f="http://www.w3schools.com/furniture">
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    Install a Connected Components Workbench to program an Allen-Bradley PLC   Guide Concept   In this guide, you'll install Rockwell Automation's Connected Components Workbench, which facilitates programming of an Allen-Bradley PLC.   You'll learn how to   Create a Rockwell Automation Account Download software from Rockwell Automation's website Install Connected Components Workbench   NOTE: The estimated time to complete this guide is 60 minutes       Step 1: Learning Path Overview   Welcome to the Rockwell Automation Learning Path!   This first guide explains the steps to get up and running with Rockwell's Connected Components Workbench, a software program to facilitate connecting to and configuring Programmable Logic Controllers, i.e. PLCs.   PLCs are commonly used in factories and other automation scenarios to control minor aspects, such as turnning particular devices on or off based on a particular situation.   Note that you don't necessarily have to run through this guide as part of the Learning Path. If you simply want to learn how to install Connected Components Workbench, this guide can still be useful to you.   But assuming you are using this guide as part of the Rockwell Automation Learning Path, then the first elements will be to install your software, i.e.:   Connected Components Workbench ThingWorx Kepware Server ThingWorx Foundation (for Windows)   You'll then connect an Allen-Bradley PLC to Connected Components Workbench and then to ThingWorx Kepware Server.   Next, we'll propogate that information further from ThingWorx Kepware Server into Foundation. Finally, we'll use Foundation's Mashup Builder to construct a GUI which can both receive and send information to the PLC.   We hope you enjoy this Learning Path.       Step 2: Signup   To access Rockwell Automation software, you first have to create an account on the Rockwell Automation website.   Go to the Rockwell Automation site.   In the top-right, click the "person symbol" for Account.   On the right, click Create an Account.   Enter a valid email address which you control and click Continue.   Enter your first and last names, your country, and click Continue.   Enter your job information and click Continue.   Enter and re-enter a password, check the EULA agreement box, and click Create Account.   Rockwell will send a verification email to the address you previously entered.   Locate the email and click Verify My Email Address.   A new browser tab will open with your verification; click Proceed to Sign In.   Sign-in with your verified email address.       Step 3: Download   Now that you have a verified Rockwell account, you will download Connected Components Workbench.   This download is a little different in that it actually has two parts.   You have to download both, and then run a built-in combiner to get access to the actual installation files.   Go to the Connected Components Workbench download site. Click Select Files. On the pop-up, check Connected Components Workbench and click Downloads. On the new pop-up, click DOWNLOAD NOW. On the download Software End-User License Agreement page, click Accept and Download. Move the download into a separate folder. Right-click on the download and select Run as administator. Agree to let the program make changes to your computer.   The download-manager will then begin the download of the actual software. Click Close when the download has completed.   Notice that there is now a new C:\RA\CCW folder.   Right-click on part1.exe and select Run as administator.   On the WinRAR self-extracting archive window, click Extract.   Notice that there is now a new "DVD" folder.   Navigate into the "DVD" folder.   Notice the Setup.exe file, which will be used to install Connected Components Workbench.       Step 4: Install   Now that you have Connected Components Workbench properly downloaded and extracted, you can begin the installation.   Right-click on Setup.exe and select Run as administrator. Click Yes to allow the program to make modifications to your computer.   Click Install now.   On the EULA screen, click Accept all.   Allow the installer to run to completion. This may take ~30 minutes..   Click Restart now to reboot and complete the installation.   After restarting, you may be asked to set your Country/Territory.   Click OK to confirm.   In the Windows "Start" menu, navigate to and expand the Rockwell Automation folder.   Click Connected Components Workbench.       Step 5: Next Steps   Congratulations! You've successfully completed the Connected Components Workbench installation guide.   In this guide, you learned how to:   Create a Rockwell Automation Account Download software from Rockwell's website Install a Connected Components Workbench   The next guide in the Using an Allen-Bradley PLC with ThingWorx learning path is Install ThingWorx Kepware Server.    Learn More    Capability Resource Manage Install ThingWorx Kepware Server   Additional Resources   For additional information on Rockwell:    Resource Link Documentation Rockwell Literature Library Documentation Connected Components Workbench
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Below is where I will discuss the simple implementation of constructing a POST request in Java. I have embedded the entire source at the bottom of this post for easy copy and paste. To start you will want to define the URL you are trying to POST to: String url = "http://127.0.0.1:80/Thingworx/Things/Thing_Name/Services/​Service_to_Post_to​"; Breaking down this url String: ​http://​ - a non-SSL connection is being used in this example 127.0.0.1:80 -- the address and port that ThingWorx is hosted on /Thingworx -- this bit is necessary because we are talking to ThingWorx /Things -- Things is used as an example here because the service I am posting to is on a Thing Some alternatives to substitute in are ThingTemplates, ThingShapes, Resources, and Subsystems /​Thing_Name​ -- Substitute in the name of your Thing where the service is located /Services -- We are calling a service on the Thing, so this is how you drill down to it /​Service_to_Post_to​ -- Substitute in the name of the service you are trying to invoke Create a URL object: URL obj = new URL(url); Class URL, included in the java.net.URL import, represents a Uniform Resource Locator, a pointer to a "resource" on the Internet. Adding the port is optional, but if it is omitted port 80 will be used by default. Define a HttpURLConnection object to later open a single connection to the URL specified: HttpURLConnection con = (HttpURLConnection) obj.openConnection(); Class HttpURLConnection, included in the java.net.HttpURLConnection import, provides a single instance to connect to the URL specified. The method openConnection is called to create a new instance of a connection, but there is no connection actually made at this point. Set the type of request and the header values to pass: con.setRequestMethod("POST"); con.setRequestProperty("Accept", "application/json"); con.setRequestProperty("Content-Type", "application/json"); con.setRequestProperty("appKey", "80aab639-ad99-43c8-a482-2e1e5dc86a2d"); You can see that we are performing a POST request, passing in an Accept header, a Content-Type header, and a ThingWorx specific appKey header. Pass true into the setDoOutput method because we are performing a POST request; when sending a PUT request we would pass in true as well. When there is no request body being sent false can be passed in to denote there is no "output" and we are making a GET request.         con.setDoOutput(true); Create a DataOutputStream object that wraps around the con object's output stream. We will call the flush method on the DataOutputStream object to push the REST request from the stream to the url defined for POSTing. We immediately close the DataOutputStream object because we are done making a request.         DataOutputStream wr = new DataOutputStream(con.getOutputStream());     wr.flush();     wr.close();           The DataOutputStream class lets the Java SDK write primitive Java data types to the ​con​ object's output stream. The next line returns the HTTP status code returned from the request. This will be something like 200 for success or 401 for unauthorized.         int responseCode = con.getResponseCode(); The final block of this code uses a BufferedReader that wraps an InputStreamReader that wraps the con object's input stream (the byte response from the server). This BufferedReader object is then used to iterate through each line in the response and append it to a StringBuilder object. Once that has completed we close the BufferedReader object and print the response we just retrieved.         BufferedReader in = new BufferedReader(new InputStreamReader(con.getInputStream()));     String inputLine;     StringBuilder response = new StringBuilder();     while((inputLine = in.readLine()) != null) {       response.append(inputLine);     }     in.close();     System.out.println(response.toString());    The InputStreamReader decodes bytes to character streams using a specified charset.         The BufferedReader provides a more efficient way to read characters from an InputStreamReader object.         The StringBuilder object is an unsynchronized method of creating a String representation of the content residing in the BufferedReader object. StringBuffer can be used instead in a case where multi-threaded synchronization is necessary.      Below is the block of code in it's entirety from the discussion above: public void sendPost() throws Exception {   String url = "http://127.0.0.1:80/Thingworx/Things/Thing_Name/Services/Service_to_Post_to";   URL obj = new URL(url);   HttpURLConnection con = (HttpURLConnection) obj.openConnection();   //add request header   con.setRequestMethod("POST");   con.setRequestProperty("Accept", "application/json");   con.setRequestProperty("Content-Type", "application/json");   con.setRequestProperty("appKey", "80aab639-ad99-43c8-a482-2e1e5dc86a2d");   // Send post request   con.setDoOutput(true);   DataOutputStream wr = new DataOutputStream(con.getOutputStream());   wr.flush();   wr.close();   int responseCode = con.getResponseCode();   System.out.println("\nSending 'POST' request to URL : " + url);   System.out.println("Response Code : " + responseCode);   BufferedReader in = new BufferedReader(new InputStreamReader(con.getInputStream()));   String inputLine;   StringBuilder response = new StringBuilder();   while((inputLine = in.readLine()) != null) {   response.append(inputLine);   }   in.close();   //print result   System.out.println(response.toString());   }
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In this blog I will be testing the SAPODataConnector using the SAP Gateway - Demo Consumption System.   Overview   The SAPODataConnector enables the connection to the SAP Netweaver Gateway through the ODdata specification. It is a specialized implementation of the ODataConnector. See Integration Connectors for documentation.   It relies on three components : Integration Runtime : microservice that runs outside of ThingWorx and has to be deployed separately, it uses Web Socket to communicate with the ThingWorx platform (similar to EMS). Integration Subsystem : available by default since 7.4 (not extension needed) Integration Connector : SAPODataConnector available by default in 8.0 (not extension needed)   ThingWorx can use OAuth to access SAP, but in this blog I will just use basic authentication.   SAP Netweaver Gateway Demo system registration   1. Create an account on the Gateway Demo system (credentials to be used on the connector are sent by email) 2. Verify that the account has access to the basic OData sample service : https://sapes4.sapdevcenter.com/sap/opu/odata/IWBEP/GWSAMPLE_BASIC/   Integration Runtime microservice setup   1. Follow WindchillSwaggerConnector hands-on (7.4) - Integration Runtime microservice setup Note: Only one Integration Runtime instance is required for all your Integration Connectors (Multiple instances are supported for High Availability and scale).   SAPODataConnector setup   Use the New Composer UI (some setting, such as API maps, are not available in the ThingWorx legacy composer)     1. Create a DataShape that is used to map the attributes being retrieved from SAP SAPObjectDS : Id (STRING), Name (STRING), Price (NUMBER) 2. Create a Thing named TestSAPConnector that uses SAPODataConnector as thing template 3. Setup the SAP Netweaver Gateway connection under TestSAPConnector > Configuration Generic Connector Connection Settings Authentication Type = fixed HTTP Connector Connection Settings Username = <SAP Gateway user> Password = < SAP Gateway pwd> Base URL : https://sapes4.sapdevcenter.com/sap Relative URL : /opu/odata/IWBEP/GWSAMPLE_BASIC/ Connection URL : /opu/odata/IWBEP/GWSAMPLE_BASIC/$metadata 4. Create the API maps and service under TestSAPConnector > API Maps (New Composer only) Mapping ID : sap EndPoint : getProductSet Select DataShape : SAPObjectDS (created at step 1) and map the following attributes : Name <- Name Id <- ProductID Price <- Price Pick "Create a Service from this mapping"     Testing our Connector   Test the TestSAPConnector::getProductSet service (keep all the input parameters blank)
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This Best Practices document should offer some guidelines and tips & tricks on how to work with Timers and Schedulers in ThingWorx. After exploring the configuration and creation of Timers and Schedulers via the UI or JavaScript Services, this document will also highlight some of the most common performance issues and troubleshooting techniques.   Timers and Schedulers can be used to run jobs or fire events on a regular basis. Both are implemented as Thing Templates in ThingWorx. New Timer and Scheduler Things can be created based on these Templates to introduce time based actions. Timers can be used to fire events in a certain interval, defined in the Timer's Update Rate (default is 60000 milliseconds = 1 minute). Schedulers can be used to run jobs based on a cron pattern (such as once a day or once an hour). Schedulers will also allow for a more detailed time based setup, e.g. based on seconds, hours, days of week or days months etc. Events fired by both Timers and Schedulers can be subscribed to with Subscriptions which can be utilized to execute custom service scripts, e.g. to generate "fake" or random demo data to update Remote Things in a test environment. In general subscriptions and scripts can be used to e.g. run regular maintenance tasks or periodically required functions (e.g. for data aggregation) For more information about setting up Timers and Schedulers it's recommended to also have a look at the following content:   How to set up and configure Timers How to set up and configure Schedulers How to create and configure Timers and Schedulers via JavaScript Services Events and Subscriptions for Timers and Schedulers   Example   The following example will illustrate on how to create a Timer Thing updating a Remote Thing using random values. To avoid any conflicts with permissions and visibility, use the Administrator user to create Things.   Remote Thing   Create a new Thing based on the Remote Thing Template, called myRemoteThing. Add two properties, numberA and numberB - both Integers and marked as persistent. Save myRemoteThing. Timer Thing   Create a new Thing based on the Timer Template, called myTimerThing. In the Configuration, change the Update Rate to 5000, to fire the Event every 5 seconds. User Context to Administrator. This will run the related services with the Administrator's user visibility and permissions. Save myTimerThing. Subscriptions   To update the myRemoteThing properties when the Timer Event fires, there are two options: Configure a Subscription on myRemoteThing and listen to Timer Events on the myTimerThing. Configure a Subscription on myTimerThing and listen to Timer Events on itself as a source. In this example, let's go with the first option and Edit myRemoteThing. Create a new Subscription pointing to myTimerThing as a Source. Select the Timer Event Note that if no source is selected, the Timer Event is not availabe, as myRemoteThing is based on the Remote Thing Template and not the Timer Template Enable the Subscription. In the Script area use the following code to assign two random numbers to the Thing's custom properties: me.numberA = Math.floor(Math.random() * 100); me.numberB = Math.floor(Math.random() * 100); Save myRemoteThing. Validation   The Subscription will be enabled and active on saving it. Switch to the myRemoteThing Properties Refreshing the Values will show updates with random numbers between 0 and 99 every 5 seconds (Timer Update Rate).   Performance considerations   Timers and Schedulers are handled via the Event Processing Subsystem. Metrics that impact current performance can be seen in Monitoring > Subsystems > Event Processing Implementing Timers and Schedulers on a Thing Template level might flood the system with services executions originating from Subscriptions to Timer / Scheduler triggered Events. Subscribing to another Thing's Events will be handled via the Event Processing Subsystem. Subscribing to an Event on the same Thing will not be handled via the Event Processing Subsystem, but rather execute on the already open in memory Thing. If Timers and Schedulers are not necessarily needed, the Services can be triggered e.g. via Data Change Events, UI Interactions etc. Recursion can be a hidden performance contributer where a Subscription to a certain Event executes a service, triggering another Event with recursive dependencies. Ensure there are no circular dependencies and service calls across Entities. If possible, reads for each and every action from disk should be avoided. Performance can be increased by storing relevant information in memory and using Streams or Datatables or for persistence. If possible, call other Services from within the Subscription instead of handling all code within the Subscription itself. For full details, see also Timers and Schedulers - Best Practice   How to identify and troubleshoot technical issues   Check the Event Processing Subsystem for any spikes in queued Events (tasks submitted) while the total number of tasks completed is not or only slowly increasing. For a historical overview, search the ApplicationLog for "Thingworx System Metrics" to get system metrics since the server has been (re-) started. In the ApplicationLog the message "Subsystem EventProcessingSubsystem is started" indicates that the Subsystem is indeed started and available. Use custom loggers in Services to get more context around errors and execution in the ScriptLog Custom Loggers can be used to identify if Events have fired and Subscriptions are actually triggered Example: logger.debug("myThing: executing subscribed service") For issues with Service execution, see also CS268218 Infinite loops in Services could render the server unresponsive and might flood the system with various Events To change the timing for a Timer, restarting the Thing is not enough. The Timer must be disabled and enabled at the desired start time. Schedulers will allow for a much more flexible timing and setting / changing execution times in advance. For further analysis it's recommended to generate Thread Dumps to get more information about the current state of Threads in the JVM. The ThingWorx Support Tools Extension can help in generating those. See also CS245547 for more information and usage.
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Key Functional Highlights ThingWorx 8.0 covers the following areas of the product portfolio:  ThingWorx Analytics, ThingWorx Utilities and ThingWorx Foundation which includes Core, Connection Server and Edge capabilities. Highlights of the release include: ThingWorx Foundation Native Industrial Connectivity: Enhancements to ThingWorx allow users to seamlessly map data from ThingWorx Industrial Connectivity to the ThingModel. With over 150 protocols supporting thousands of devices, ThingWorx Industrial Connectivity allows users to connect, monitor, and manage diverse automation devices from ThingWorx. With this new capability, users can quickly integrate industrial operations data in IoT solutions for smart, connected operations. Native AWS IoT and Azure IoT Cloud Support: ThingWorx 8 now has deeper, native integration with AWS IoT and Azure IoT Hub clouds so you can gain cost efficiencies and standardize on the device cloud provider of your choice.  This support strengthens the connection between leading cloud providers and ThingWorx. Next Generation Composer: Re-imagined Composer using modern browser concepts to improve developer efficiency including enhanced functionality, updated user interface and optimized workflows. Product Installers:  New, Docker-based product installers for Foundation and Analytics make it easy and fast for customers to get the core platform and analytics server running. Single Sign On (SSO): Provides the ability to login once and access all PTC apps and enterprise systems. License Management: Simple, automated, licensing system for collection, storage, reporting, management and auditing of licensing entitlements. Integration Connectors: Integration Connectors allow Thingworx developers and administrators quick and easy access to the data stored on external ERP, PLM, Manufacturing and other systems to quickly develop applications providing improved Contextualization and Analysis. Thingworx 8.0 delivers ‘OData’ and ‘SAP OData’ connectors plus the ability to connect to generic web services to supplement the ‘Swagger’ and ‘Windchill Swagger’ Connectors released in Thingworx 7.4. An improved mapping tool allows Business Administrators to quickly and easily transform retrieved data into a standard Thingworx format for easy consumption. Includes single sign on support for improved user experience. ThingWorx Analytics Native Anomaly Detection: ThingWorx 8 features more tightly integrated analytics capabilities, including the ability to configure anomaly alerts on properties directly from the ThingWorx Composer. ThingWatcher technology is utilized to increase machine monitoring capabilities by automatically learning normal behavior, continuously monitoring data streams and raising alerts when abnormal conditions are identified. ThingWorx Utilities Software Content Management (SCM) – Auto Retry: Provides the ability to automatically retry delivery of patches to devices if interrupted.  This ensures the ability to successfully update devices.  ThingWorx Trial Edition ThingWorx Trial Edition will be available to internal PTC resources at launch and will be made available externally on the Developer Portal shortly after launch. Developer Enablement: Enhancements have been made to the Trial Edition installation tool, providing a native installation process of the ThingWorx platform including: ThingWorx Foundation ThingWorx Utilities ThingWorx Analytics ThingWorx Industrial Connectivity Documentation ThingWorx 8.0 Reference Documents ThingWorx Analytics 8.0 Reference Documents ThingWorx Core 8.0 Release Notes ThingWorx Core Help Center ThingWorx Edge SDKs and WebSocket-based Edge MicroServer Help Center ThingWorx Connection Services Help Center ThingWorx Industrial Connectivity Help Center ThingWorx Utilities Help Center ThingWorx Utilities Installation Guide ThingWorx Analytics Help Center ThingWorx Trial Edition User Guide Additional information ThingWorx eSupport Portal ThingWorx Developer Portal ThingWorx Marketplace Download The following items are available for download from the PTC Software Download site. ThingWorx Platform – Select Release 8.0 ThingWorx Utilities – Select Release 8.0 ThingWorx Analytics – Select Release 8.0 You can also read this post in the Developer Community from Jeremy Little about the technical changes in ThingWorx 8.0.
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I created this recently for another group -  might be useful    Video Link to Create a Database connection to you Postgres Thingwork Database 
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Installing an Open Source Time Series Platform For testing InfluxDB and its graphical user interface, Chronograf I'm using Docker images for easy deployment. For this post I assume you have worked with Docker before.   In this setup, InfluxDB and Chronograf will share an internal docker network to exchange data.   InfluxDB can be accessed e.g. by ThingWorx via its exposed port 8086. Chronograf can be accessed to administrative purposes via its port 8888. The following commands can be used to create a InfluxDB environment.   Pull images   sudo docker pull influxdb:latest sudo docker pull chronograf:latest   Create a virtual network   sudo docker network create influxdb   Start the containers   sudo docker run -d --name=influxdb -p 8086:8086 --net=influxdb --restart=always influxdb sudo docker run -d --name=chronograf -p 8888:8888 --net=influxdb --restart=always chronograf --influxdb-url=http://influxdb:8086     InfluxDB should now be reachable and will also restart automatically when Docker (or the Operating System) are restarted.
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NOTE: Even though I have tried on ODataConnector and SwaggerConnector, these steps below should be working for all the Thingworx Integration Connectors viz. GenericConnector, HTTPConnector, ODataConnector, SAPODataConnector, SwaggerConnector, WindchillSwaggerConnector.   This document guides you to add a custom header in any Thingworx Integration connector. Step 1. Create a Datashape say "CustomHeadersDataShape" and add a string field with Name the same as the header name you want to add. In this case, I want to add a header called "Prefer" so it will look something like              Step 2: Go to the Integration Connector which you want to add this custom header. Navigate to "Services". Under the "Inherited Services", edit/overwrite the "GetCustomHeaderParameters" service by clicking on the edit (pencil) icon. Step 3: In the JavaScript Code sniped section add below code snipped   var params = { infoTableName : "InfoTable", dataShapeName : "CustomHeadersDataShape" }; var result = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape(params); var preferValue = "odata.maxpagesize=50"; var newRow = {"Prefer" : preferValue }; result.AddRow(newRow);   Step 4: Save the service and execute "GetCustomHeaderParameters". You should see something like         Now your custom header "Prefer: odata.maxpagesize=50" is set. further execution of your connector services will consider this header until it is reset.
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Internationalization and Localization Internationalization (often abbreviated I18N – from "I" + 18 more letters + "n") is the process of developing software that supports many languages, including those with non-Latin character sets. Localization (L10N) refers to developing applications that can be delivered in many languages, relying on the underlying architecture of I18N. This how-to article focuses mostly on localization, since the infrastructure is in place and stable. Create a Localization Table You create a Localization Table entity when you need to add support for another language to the application you're developing. Someone from Sales has said "There's an opportunity if we can deliver the Spiffy application in Estonian." This suggests that an Estonian-speaking end user should be able to run Spiffy and see all of its labels, messages, prompts, dialogs, and so on in Estonian. Most of the cost of adding Estonian language support is in a (usually contracted) service that does the English-to-Estonian (or whatever target language) translations. Such services employ native speakers who can get the nuances of translation correct. See Tips for translators below for suggestions on improving the accuracy of the translation. In Composer, view the Localization Tables list. Begin by duplicating an existing table (e.g. check Default or another language and click Duplicate) or by clicking New. A new tab will open with a New Localization Table in edit mode. The fields shown are: Locale (required). This is the official language tag of the new language. Language tags are defined by an Internet standard, IETF BCP 47. Briefly, they consist of a standard abbreviation for a language (e.g. en for English, de for German), followed optionally by a script subtag (e.g. Cyrl for Cyrilic), followed optionally by a region code (a country code, such as CH for Switzerland or HK for Hong Kong, or a U.N. region number), followed optionally by other qualifiers such as dialect. A simple example is es, Spanish. A complex one is sl-Latn-IT-nedis, Slovenian rendered in Latin characters as spoken in Italy in the Natisone dialect. Software rarely needs such highly specific language tags; the most specific practical examples are the various scripts and regions for Chinese (e.g. zh-Hans-CN, zh-Hant-TW). Language Name (Native) (required). This is the name of the language as written in that language, such that it would be readable by a native speaker. For example, 日本語 for Japanese, ਪੰਜਾਬੀ ਦੇ for Punjabi, or Deutsche for German. Language Name (Common). This is the name of the language as written in a common administrative language. For an application delivered internationally, English is probably a safe choice. Administrators at a customer site might change these to be in the language of the headquarters country. Description. Free form text describing the language. This will appear to end-users as a tooltip as they hover over language choices. Tags. Standard ThingWorx entity tags. Home Mashup. Does not apply. Avatar. An icon for this language. The default is . No other icons are delivered as standard, but language selection interfaces in many products use national flags to help distinguish choices, and those could be supplied here. Avatars are 48x48px images. There may be political implications in choosing a flag or other symbol for a language; use caution. Note that subtags of a language tag are separated by a hyphen, as in zh-Hans-SG. Using underscore is a Java convention that does not conform to BCP 47.A complete properties definition for Czech might look like this: Once the table has been created and saved, you can edit the translated text in Composer. Under Entity Information, select Localization Tokens. A grid similar to this will appear: The columns shown are: Token Name. This is the symbol used by mashup developers to insert a localized string into a certain place in a widget. For example, no matter how the phrase "Add New Page" is rendered (Neue Seite hinzufügen, Adicionar nova página, 새 페이지 추가...) the application developer is only concerned that the token addNewPage appears on the proper widget. See How tokens are resolved below for more information. This Language. How the text is to be represented in this language, that is, the language of the Localization Table currently being viewed or edited. Language. How the text has already been represented in any other language currently defined on the system. This is simply for reference purposes, to compare one translation with another. Usage. Can be set to Label, Message, or left unspecified. This is a guide to translators, who have to be concerned about the size of translated text. Usage Label suggests that the text needs to fit in a confined space, such as in a column header or on the face of a button. Usage Message suggests that the text is meant for a popup, error message, help, or somewhere that full sentences can be accommodated. Context. This is a free-form text field to provide instructions, advice, context, or other explanatory material to the translator. For the token book, for example, the context field can distinguish between the senses of book (something to read), book a table, book a sale, or book a prisoner, which may all have different translations. Translations can be entered in Composer. However, it's also likely that a third-party translator will do the work without using this editor. See Tips for translators below. Define language preferences for a user The reason for localization is to present user interfaces in the best language for a given user. To support this, each ThingWorx user is associated with one or more languages – those that that user can read comfortably. Some applications might offer just one language or a few, some many, and the supported languages may or may not overlap. So each user defines an ordered preference list, saying in effect: my best language is Catalan, but I'm decent in Spanish, and if those aren't available I did spend a few years in Hungary, and as a last resort there was some French in school. This would be represented in ThingWorx as: ca,es,hu,fr. A user from Scotland might have language preference en-UK,en, meaning that English with United Kingdom spellings and vocabulary is best (tyre, windscreen), but if not available then any English will do (tire, windshield). (It is not necessary to spell out related preferences of this type – see How tokens are resolved.) Any application then interacts with a given user in the best language that the application and user have in common.To define the language preference(s) for a user, open the Users list in Composer: Then choose an existing user to edit, or click New to create a new account. The only localization related information here is the Languages field. An administrator who knows the names of available languages may edit or paste an ordered, comma-separated list into the Languages field (e.g.  ca,es,hu,fr-CA). Clicking the Edit... button brings up a drag-and-drop preferences editor: The column on the left shows available (unselected) languages. The column on the right shows this user's languages, with the top entry being the most preferred language. Dragging a language from left to right adds it to the user's list; from right to left removes it; dragging rows up and down on the right changes the preference order. As language entries are dragged, a highlight appears to show where they might be dropped: A user with no language preference set will have all tokens resolved from the Default and System tables. Language Preferences can be set programmatically, as detailed in KCS Article CS243270. Localize Mashups The job of the application developer is to keep hard-coded natural language strings out of applications. To support this, widgets define an attribute isLocalizable: true for widget properties that can contain text. This shows up in the Mashup editor as a globe icon next to each localizable property. In this example, both the Text and ToolTipField properties are localizable: Clicking the globe icon changes the property from static to localized. The appearance in the Mashup editor changes accordingly: Clicking the magic wand icon opens the localization token picker: The list of tokens on the right corresponds to the Token Name column in the Localization Table editor. This is the key that is common to the meaning of a word or phrase, independent of its translation into natural languages. Select one from the list, or click to create a new one. Enter the token name and its Default (usually English) value: Note that, complying with best practices for extension developers, the token name has been namespaced: this token belongs to Acme Inc.'s Spiffy application. The rest of the name is descriptive and may reflect other development standards.When a new token is created, it becomes available to edit in every configured Localization Table. If these are not updated, then the default (English) value will be shown wherever the token occurs. How tokens are resolved What happens at run time when the UI needs to display the value of a localization token? The answer is determined by the current user's language preferences the set of Localization Tables configured on the system the presence or absence of a translation for a given token in a given table To visualize this, picture the user's language preferences as a stack, with the most preferred language on top and the least one sitting on the floor – where the floor consists of the Default and System Localization Tables: The user's language preference is fr,pt,ru,hi (French, Portuguese, Russian, Hindi, with French most preferred). The system is configured with Localization Tables, which have no order, for it (Italian), fr-CA (Canadian French), ru (Russian), pt-BR(Brazilian Portuguese), es (Spanish), and the default (likely Engish). Now the UI needs to present this user with the best value for the token com.acme.spiffy.labelAssembly. To resolve this, we start at the top of the stack. Is there a fr Localization Table? There is. Does it contain a translation for com.acme.spiffy.labelAssembly? For the sake of illustration, assume that it does not – perhaps other applications have French support, but the Spiffy application doesn't, so there aren't any com.acme.spiffy.* tokens in the French Localization Table. So we still need a value. Continuing down through the user's preferences, the next acceptable language is pt. Is there a pt localization table? No. There is a Brazilian Portuguese translation, but that won't help a user from Portugal. Still looking, we move to the next language, ru. Is there a ru Localization Table? There is. Does it contain a translation forcom.acme.spiffy.labelAssembly? It does: Ассамблея – so the token has a value, and that is what gets displayed in the UI. Suppose that the user's preferences were more specific, something like this: The users's language preference is fr-CA,pt-BR,ru-Cyrl-RU,sl-Latn-IT-nedis (Canadian French, Brazilian Portuguese, Russian in Cyrillic characters as used in Russia, Slovenian in Latin characters as used in Italy where the Natisone River dialect prevails). ThingWorx treats this by internally expanding the stack to include acceptable fall-back languages. In effect, it looks like: Of the four languages that the user can accept and that the system defines (fr-CA, fr, pt-BR, ru) the first one containing the desired token determines its value in the UI. Token and translation management for applications While it's possible to edit localized values using the Localization Table editor in Composer, translations are usually done in bulk by subject-matter experts. While workflow will vary among organizations and projects, the following example illustrates the basic process. ACME, Inc. is developing a ThingWorx application called Cambot for controlling security cameras. ACME's developer begins by constructing a mashup: This is the first draft. There is an area for the video widget, to be added later, and some button and label widgets for choosing and controlling a camera. The widgets have been given static labels: As shown here, the text for the pan left button has been entered simply as "Pan Left." But the Cambot app needs to be localized, and delivered in English, French, and Spanish. The next step for the developer is to replace all of the static text with localization tokens. Clicking the globe icon to the left of the label property changes the text from static to tokenized: and adds a magic picker for localization tokens. This is a new application, and will need its own set of localization tokens. To create the one for "Pan Left," click the magic wand to open the tokens picker: and then click "+ Localization Token" to add a new one. A dialog opens prompting for the token name and its default (English) value: Note that the token name has been namespaced for two reasons: to prevent conflicts with tokens from other sources, and to allow the developer and translators to work only with application-specific tokens. On clicking "Add Localization Token," the token is created and the default value saved. The mashup builder now shows: . After all of the tokens needed by the application have been defined, they and their values may be seen on the Localization Tokens editor for the Default Localization Table. By entering the namespace prefix in the filter textbox, the display can be restricted to the tokens for this application: As application development continues, and more tokens are required, this process is repeated. When tokens are defined, the developer should edit the Default Localization Table to supply Usage and Context information for each one: Finally, it's time to do the translations for French and Spanish. First, create the localization tables for those languages, as described above in "Create a Localization Table." From the Import/Export menu, select EXPORT / To File: Then, depending on the file format desired, choose either the Entities or Single Entity tab. For Entities, set the Collections value to Localization Tables, enter the namespace in the Token Prefix field, and choose XML as the Export Type: This will produce a single output file, containing a Localization Table element for every language defined on the system – in this example, English, French, and Spanish -- but including only the com.acme.cambot tokens. For Single Entity, choose the language to export, specify the prefix, and choose XML: This must be repeated, once for each language, and creates a separate XML file for each. In either case, the translator should be supplied with the Default XML and the file for the language to be added. (Or, the tokens and values may be converted to and from other formats, depending on the requirements of the translation service. In any case, the translated values must be in the same XML format before they can be imported.) The Default export file will contain a <Rows> element like this: < Rows >     < Row >         < usage > <![CDATA[label]]> </ usage >         < name > <![CDATA[com.acme.cambot.buttonnext]]> </ name >         < context > <![CDATA[Button to switch view to next camera]]> </ context >         < value > <![CDATA[Next Camera]]> </ value >     </ Row >     < Row >         < usage > <![CDATA[label]]> </ usage >         < name > <![CDATA[com.acme.cambot.buttonpanleft]]> </ name >         < context > <![CDATA[Button to pan view to the left]]> </ context >         < value > <![CDATA[Pan Left]]> </ value >     </ Row >     < Row >         < usage > <![CDATA[label]]> </ usage >         < name > <![CDATA[com.acme.cambot.buttonpanright]]> </ name >         < context > <![CDATA[Button to pan view to the right]]> </ context >         < value > <![CDATA[Pan Right]]> </ value >     </ Row >     < Row >         < usage > <![CDATA[label]]> </ usage >         < name > <![CDATA[com.acme.cambot.buttonprev]]> </ name >         < context > <![CDATA[Button to switch view to previous camera]]> </ context >         < value > <![CDATA[Prev. Camera]]> </ value >     </ Row >     < Row >         < usage > <![CDATA[label]]> </ usage >         < name > <![CDATA[com.acme.cambot.buttontiltdown]]> </ name >         < context > <![CDATA[Button to tilt view down]]> </ context >         < value > <![CDATA[Tilt Down]]> </ value >     </ Row >     < Row >         < usage > <![CDATA[label]]> </ usage >         < name > <![CDATA[com.acme.cambot.buttontiltup]]> </ name >         < context > <![CDATA[Button to tilt view up]]> </ context >         < value > <![CDATA[Tilt Up]]> </ value >     </ Row >     < Row >         < usage > <![CDATA[label]]> </ usage >         < name > <![CDATA[com.acme.cambot.buttonzoomin]]> </ name >         < context > <![CDATA[Button to view more detail]]> </ context >         < value > <![CDATA[Zoom In]]> </ value >     </ Row >     < Row >         < usage > <![CDATA[label]]> </ usage >         < name > <![CDATA[com.acme.cambot.buttonzoomout]]> </ name >         < context > <![CDATA[Button to expand view]]> </ context >         < value > <![CDATA[Zoom Out]]> </ value >     </ Row >     < Row >         < usage > <![CDATA[label]]> </ usage >         < name > <![CDATA[com.acme.cambot.labelcamera]]> </ name >         < context > <![CDATA[Label for current camera name]]> </ context >         < value > <![CDATA[Camera:]]> </ value >     </ Row >     < Row >         < usage > <![CDATA[label]]> </ usage >         < name > <![CDATA[com.acme.cambot.labelrecording]]> </ name >         < context > <![CDATA[Notice displayed when camera is recording]]> </ context >         < value > <![CDATA[Recording]]> </ value >     </ Row > </ Rows > Whereas the French and Spanish export files will contain an empty <Rows/> element. This is where the new translations should be added. When the translations are ready, check that the <LocalizationTable> attributes (name, description, languageCommon, languageNative) are correct. Then import the new languages and inspect the results using the Localization Table editor. Localization tables for an application may be bundled into an extension .zip file as other entities are handled; on import, the tokens for the application will be merged with existing localization tables for the same language. In the case that a brand new language is being introduced, note that many widgets use tokens from the System localization table. These will need to be translated as well – however, there is no easy way to restrict the set of tokens to those actually used. At present this is a manual filtering step. For existing languages, check to see if the System tokens have already been translated. Important note on character encoding In handling the export, transmission and editing of XML files, it's important to ensure that UTF-8 encoding is maintained throughout. Encoding problems can show up either as errors when the file is re-imported, or as localized strings with question marks or other unexpected characters in place of accented letters. ThingWorx must run with UTF-8 as the default file encoding. Specify the Java option -Dfile.encoding=UTF-8 on launch. Windows In %CATALINA_HOME%\bin\setenv.bat, include this command:     set CATALINA_OPTS=-Dfile.encoding=UTF-8 Tips for translators Each token in an exported Localization Table XML file is defined by four fields: name, value, usage, and context. While name might be suggestive, it is actually arbitrary and should not be relied on. Value contains the natural language value for the token in another language (as agreed upon). Translating from this language into the target language is the object. Usage hints at constraints on the size of the translated text. ThingWorx widgets do not in general resize to fit contents; so a button label, column heading, field label, etc. may be more difficult to translate. Because the default language is likely to be English, and English is a particularly compact language, the application may have been designed with narrow constraints. Such tokens should be marked as tricky by having a usage value of Label. Tokens with a usage of Message are for strings in more adaptable spaces, such as a texarea, warning message, etc. Context allows the application developer to provide translation hints. This may disambiguate synonyms, explain usage, discuss space constraints, specify tone of voice, or anything else applicable. The interesting section of a language's XML representation is contained in the <Rows> element. For example: <Rows> example 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 < Rows >     < Row >         < usage />         < name > <![CDATA[com.acme.spiffy.labelPart]]> </ name >         < context />         < value > <![CDATA[Part]]> </ value >     </ Row >     < Row >         < usage > <![CDATA[Label]]> </ usage >         < name > <![CDATA[com.acme.spiffy.labelAssembly]]> </ name >         < context > <![CDATA[Label identifying the name of the assembly being edited, appears as Assembly: external_name]]> </ context >         < value > <![CDATA[Assembly]]> </ value >     </ Row >     < Row >         < usage > <![CDATA[Message]]> </ usage >         < name > <![CDATA[com.acme.spiffy.warningIncomplete]]> </ name >         < context > <![CDATA[Pop-up warning message on Save]]> </ context >         < value > <![CDATA[A referenced part is missing, undefined, or not allowed in this assembly.]]> </ value >     </ Row > </ Rows > In this example, the token defined in lines 2 through 7 is missing the translation cues usage and context. The translator's only option is to intuit the sense of "Part" – is it a noun or a verb? – and attempt a reasonable guess. Access to a running example of the application would clearly be helpful. Lines 8 through 13 identify a label and describe how it is used; lines 14 through 19 do the same for a message. The translator would know that space for the translation of "Assembly" might be limited but that the warning message can be expressed naturally. A translator working on French might then edit this file as follows (again, only the <Rows> element is illustrated): After translating 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 < Rows >     < Row >         < usage />         < name > <![CDATA[com.acme.spiffy.labelPart]]> </ name >         < context />         < value > <![CDATA[Partie]]> </ value >     </ Row >     < Row >         < usage > <![CDATA[Label]]> </ usage >         < name > <![CDATA[com.acme.spiffy.labelAssembly]]> </ name >         < context > <![CDATA[Label identifying the name of the assembly being edited, appears as Assembly: external_name]]> </ context >         < value > <![CDATA[Assemblée]]> </ value >     </ Row >     < Row >         < usage > <![CDATA[Message]]> </ usage >         < name > <![CDATA[com.acme.spiffy.warningIncomplete]]> </ name >         < context > <![CDATA[Pop-up warning message on Save]]> </ context >         < value > <![CDATA[Une partie référencé est manquant, indéfini, ou non autorisés dans cette assemblée.]]> </ value >     </ Row > </ Rows > Note that only the <value> elements need to be translated – the context and usage are hints for the translator. System tokens for international data formats There are several tokens used for formatting that are also subject to localization. Token Default value Notes datepickerDayNamesMin Su,Mo,Tu,We,Th,Fr,Sa Day-of-week abbreviations used in calendar heading. datepickerFirstDay 0 First day of the week, 0 for Sunday, 1 for Monday... datepickerMonthNames January,February,March,April,May,June,July,August,September,October,November,December Month names used in calendar heading. dateTimeFormat_Default yyyy-MM-dd HH:mm:ss Date and time format codes are defined by the moment.js library. dateTimeFormat_FullDateTime LLLL dateTimeFormat_LongDate LL dateTimeFormat_LongDateTime LLL dateTimeFormat_MediumDate ll dateTimeFormat_ShortDate l dateTimeFormat_TimeOnly LT shortDateFormat mm/DD/yyyy See also KCS Article CS241828​ for details about numeric localization. Allowing users to set their own language preferences It may not be practical for the Administrator to set the language preferences for each user. An application may elect to expose the preferences editor to the end user, so that each user may select from the available languages those that are useful. To support this, ThingWorx Composer offers a Preferences widget in the Mashup builder. The widget may be inserted into any application wherever the designer chooses. It may be tied to a button or menu item, or simply appear in a layout with other widgets – perhaps along with application-specific preferences and other settings. To use the Preferences widget, design a mashup for it to appear in. The minimal case would be a responsive page mashup containing nothing but the preferences widget. Add the Preferences widget by dragging it into place: A placeholder for the widget appears in the mashup: The widget may be customized by setting various properties: These properties are specific to the Preferences widget: ShowClearRecent: Check this to include the option for the user to clear the Most Recently Used history. You may specify a localized tooltip. ShowRestoreTabs: Check this to include the option for the user to set tab restoration to ask, always, or never. You may specify a localized tooltip. ShowLanguages: Check this to include the option for the user to edit language preferences. You may specify a localized tooltip. ShowUserName: Check this to label the preferences widget with the user's name. ShowUserAvatar: Check this to label the preferences widget with the user's avatar, if one is defined. Style: Style the preferences widget itself. ButtonStyle: Style the Clear Recent and Edit buttons. These should probably be set to the application's primary button style. After adding the Preferences widget to a mashup, provide some way for the user to navigate to it, consistent with the application's UI design. The mashup may be tied to a menu entry, or assigned to a Navigation widget, or included in a page within the application's workflow – whatever suits the application design. Here is an example of providing access to preferences through a button in the application's title area: 1) The Navigation widget is placed in the page header. 2) The MashupName property is set to the mashup containing a Preferences widget. 3) The TargetWindow property is set to Modal Popup. 4) For a more interesting UI, the button label is bound from the user's name. At runtime, the example looks like this: Note that there is also a menu item leading to the mashup with the Preferences widget.
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1. Add an Json parameter Example: { ​    "rows":[         {             "email":"example1@ptc.com"         },         {             "name":"Qaqa",             "email":"example2@ptc.com"         }     ] } 2. Create an Infotable with a DataShape usingCreateInfoTableFromDataShape(params) 3. Using a for loop, iterate through each Json object and add it to the Infotable usingInfoTableName.AddRow(YourRowObjectHere) Example: var params = {     infoTableName: "InfoTable",     dataShapeName : "jsontest" }; var infotabletest = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape(params); for(var i=0; i<json.rows.length; i++) {     infotabletest.AddRow({name:json.rows.name,email:json.rows.email}); }
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Everywhere in the Thingworx Platform (even the edge and extensions) you see the data structure called InfoTables.  What are they?  They are used to return data from services, map values in mashup and move information around the platform.  What they are is very simple, how they are setup and used is also simple but there are a lot of ways to manipulate them.  Simply put InfoTables are JSON data, that is all.  However they use a standard structure that the platform can recognize and use. There are two peices to an InfoTable, the DataShape definition and the rows array.  The DataShape is the definition of each row value in the rows array.  This is not accessible directly in service code but there are function and structures to manipulate it in services if needed. Example InfoTable Definitions and Values: { dataShape: {     fieldDefinitions : {           name: "ColOneName", baseType: "STRING"     },     {           name: "ColTwoName", baseType: "NUMBER"     }, rows: [     {ColOneName: "FirstValue", ColTwoName: 13},     {ColOneName: "SecondValue, ColTwoName: 14}     ] } So you can see that the dataShape value is made up of a group of JSON objects that are under the fieldDefinitions element.  Each field is a "name" element, which of course defined the field name, and the "baseType" element which is the Thingworx primitive type of the named field.  Typically this structure is automatically created by using a DataShape object that is defined in the platform.  This is also the reason DataShapes need to be defined, so that fields can be defined not only for InfoTables, but also for DataTables and Streams.  This is how Mashups know what the structure of the data is when creating bindings to widgets and other parts of the platform can display data in a structured format. The other part is the "rows" element which contains an array of of JSON objects which contain the actual data in the InfoTable. Accessing the values in the rows is as simple as using standard JavaScript syntax for JSON.  To access the number in the first row of the InfoTable referenced above (if the name of the InfoTable variable is "MyInfoTable") is done using MyInfoTable.rows[0].ColTowName.  This would return a value of 13.  As you can not the JSON array index starts at zero. Looping through an InfoTable in service script is also very simple.  You can use the index in a standard "for loop" structure, but a little cleaner way is to use a "for each loop" like this... for each (row in MyInfoTable.rows) {     var colOneVal = row.ColOneName;     ... } It is important to note that outputs of many base services in the platform have an output of the InfoTable type and that most of these have system defined datashapes built into the platform (such as QueryDataTableEntries, GetImplimentingThings, QueryNumberPropertyHistory and many, many more).  Also all service results from query services accessing external databases are returned in the structure of an InfoTable. Manipulating an InfoTable in script is easy using various functions built into the platform.  Many of these can be found in the "Snippets" tab of the service editor in Composer in both the InfoTableFunctions Resource and InfoTable Code Snippets. Some of my favorites and most commonly used... Create a blank InfoTable: var params = {   infoTableName: "MyTable" }; var MyInfoTable= Resources["InfoTableFunctions"].CreateInfoTable(params); Add a new field to any InfoTable: MyInfoTable.AddField({name: "ColNameThree", baseType: "BOOLEAN"}); Delete a field: MyInfoTable.RemoveField("ColNameThree"); Add a data row: MyInfoTable.AddRow({ColOneName: "NewRowValue", ColTwoName: 15}); Delete one or more data row matching the values defined (Note you can define multiple field in this statement): //delete all rows that have a value of 13 in ColNameOne MyInfoTable.Delete({ColNameOne: 13}); Create an InfoTable using a predefined DataShape: var params = {   infoTableName: "MyInfoTable",   dataShapeName: "dataShapeName" }; var MyInfoTable = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape(params); There are many more functions built into the platform, including ones to filter, sort and query rows.  These can be extremely useful when tying to return limited or more strictly structured InfoTable data.  Hopefully this gives you a better understanding and use of this critical part of the Thingworx Platform.
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I have created a mashup which allows you to easily use and test the Prescriptions functionality in Thingworx Analytics (TWA). This is where you choose 1 or more fields for optimization, and TWA tells you how to adjust those fields to get an optimal outcome.   The functionality is based on a public sample dataset for concrete mixtures, full details are included in the attached documentation.  
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Persistent vs. Logged Properties By Mike Jasperson, VP of IoT EDC   Executive Summary ThingWorx provides several different “aspects” (or storage options) for how property values are saved.  These options each have different implications for performance and scalability.  Understanding those implications is important for designing a scalable IOT solution.   Persistent Properties are best used for non-telemetry data which will change infrequently (for example only a few times in a day) and where historical values are not required.  When overused, Persistent properties can put significant pressure on the database layer of your ThingWorx implementation, leading to poor performance of your IOT application.  As the number of Things in your IOT application scales up, the quantity or frequency of persistent properties per Thing needs to be carefully considered.   Logged Properties are best used for telemetry data where historical values need to be retained, but also for any other value that is expected to change frequently.  Logged properties can create some additional requirements: a process for handling null/default values after restarts, more disk space, and a data retention policy. There are benefits as well, though, like more flexibility and scalability for the ingestion of larger volumes of data.   Persistent + Logged Properties perform database operations of both aspects.  Combined use should be very limited – only properties that update infrequently (a few times a day), and that must be in-memory in the event of a ThingWorx restart.   In-Memory Only Properties are neither persistent nor logged – they are not stored to the database.  These properties can greatly improve scale for values that need to be available for the application to drive UIs or compute other derived values that will be stored.  However, high-frequency updates of in-memory properties can create scale challenges in HA (high availability) ThingWorx configurations where memory state needs to be constantly shared between multiple ThingWorx nodes.     Find a complete summary as well as example cases in the document attached.
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The following code is best practice when creating any "entity" in Thingworx service script.  When a new entity is created (like a Thing) it will be loaded into the JVM memory immediately, but is not committed to disk until a transaction (service) successfully completes.  For this reason ALL code in a service must be in a try/catch block to handle exceptions.  In order to rollback the create call the catch must call a delete for any entity created.  In line comments give further detail.     try {     var params = {         name: "NewThingName",         description: "This Is A New Thing",         thingTemplateName: "GenericThing"     };     Resources["EntityServices"].CreateThing(params);    // Always enable and restart a new thing to make it active on the Platform     Things["NewThingName"].Enable();     Things["NewThingName"].Restart();       //Now Create an Organization for the new Thing     var params = {         topOUName: "NewOrgName",         name: "NewOrgName",         description: "New Orgianization for new Thing",         topOUDescription: "New Org Main"     };     Resources["EntityServices"].CreateOrganization(params);       // Any code that could potentially cause an exception should     // also be included in the try-catch block. } catch (err) {     // If an exception is caught, we need to attempt to delete everything     // that was created to roll back the entire transaction.     // If we do not do this a "ghost" entity will remain in memory     // We must do this in reverse order of creation so there are no dependency conflicts     // We also do not know where it failed so we must attempt to remove all of them,     // but also handle exceptions in case they were not created       try {         var params = {name: "NewOrgName"};         Resources["EntityServices"].DeleteOrganization(params);     }     catch(ex2) {//Org was not created     }       try {         var params = {name: "NewThingName"};         Resources["EntityServices"].DeleteThing(params);     }     catch(ex2) {//Thing was not created     } }
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