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Posted to commits@edgent.apache.org by qu...@apache.org on 2016/07/26 21:33:19 UTC
[49/51] [partial] incubator-quarks-website git commit: [QUARKS-233]
Rename Quarks to Edgent * text references * image references * placeholder
logos * Javadoc
http://git-wip-us.apache.org/repos/asf/incubator-quarks-website/blob/05ad5e88/site/docs/home.md
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diff --git a/site/docs/home.md b/site/docs/home.md
index 6a9c01b..11d5464 100644
--- a/site/docs/home.md
+++ b/site/docs/home.md
@@ -6,23 +6,23 @@ type: first_page
homepage: true
---
-## Apache Quarks overview
+## Apache Edgent overview
Devices and sensors are everywhere, and more are coming online every day. You need a way to analyze all of the data coming from your devices, but it can be expensive to transmit all of the data from a sensor to your central analytics engine.
-Quarks is an open source programming model and runtime for edge devices that enables you to analyze data and events at the device. When you analyze on the edge, you can:
+Edgent is an open source programming model and runtime for edge devices that enables you to analyze data and events at the device. When you analyze on the edge, you can:
* Reduce the amount of data that you transmit to your analytics server
* Reduce the amount of data that you store
-A Quarks application uses analytics to determine when data needs to be sent to a back-end system for further analysis, action, or storage. For example, you can use Quarks to determine whether a system is running outside of normal parameters, such as an engine that is running too hot.
+An Edgent application uses analytics to determine when data needs to be sent to a back-end system for further analysis, action, or storage. For example, you can use Edgent to determine whether a system is running outside of normal parameters, such as an engine that is running too hot.
-If the system is running normally, you don\u2019t need to send this data to your back-end system; it\u2019s an added cost and an additional load on your system to process and store. However, if Quarks detects an issue, you can transmit that data to your back-end system to determine why the issue is occurring and how to resolve the issue.
+If the system is running normally, you don\u2019t need to send this data to your back-end system; it\u2019s an added cost and an additional load on your system to process and store. However, if Edgent detects an issue, you can transmit that data to your back-end system to determine why the issue is occurring and how to resolve the issue.
-Quarks enables you to shift from sending a continuous flow of trivial data to the server to sending only essential and meaningful data as it occurs. This is especially important when the cost of communication is high, such as when using a cellular network to transmit data, or when bandwidth is limited.
+Edgent enables you to shift from sending a continuous flow of trivial data to the server to sending only essential and meaningful data as it occurs. This is especially important when the cost of communication is high, such as when using a cellular network to transmit data, or when bandwidth is limited.
-The following use cases describe the primary situations in which you would use Quarks:
+The following use cases describe the primary situations in which you would use Edgent:
* **Internet of Things (IoT)**: Analyze data on distributed edge devices and mobile devices to:
- Reduce the cost of transmitting data
@@ -40,7 +40,7 @@ The following environments have been tested for deployment on edge devices:
### Edge devices and back-end systems
-You can send data from an Apache Quarks application to your back-end system when you need to perform analysis that cannot be performed on the edge device, such as:
+You can send data from an Apache Edgent application to your back-end system when you need to perform analysis that cannot be performed on the edge device, such as:
* Running a complex analytic algorithm that requires more resources, such as CPU or memory, than are available on the edge device
* Maintaining large amounts of state information about a device, such as several hours worth of state information for a patient\u2019s medical device
@@ -50,7 +50,7 @@ You can send data from an Apache Quarks application to your back-end system when
- Data of record, such as a patient\u2019s medical history or trucking manifests
- Data from other devices
-Quarks communicates with your back-end systems through the following message hubs:
+Edgent communicates with your back-end systems through the following message hubs:
* MQTT \u2013 The messaging standard for IoT
* IBM Watson IoT Platform \u2013 A cloud-based service that provides a device model on top of MQTT
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http://git-wip-us.apache.org/repos/asf/incubator-quarks-website/blob/05ad5e88/site/docs/overview.md
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diff --git a/site/docs/overview.md b/site/docs/overview.md
index e0c454d..5a791c1 100644
--- a/site/docs/overview.md
+++ b/site/docs/overview.md
@@ -2,22 +2,22 @@
title: Overview
---
-# Apache Quarks Overview
+# Apache Edgent Overview
Devices and sensors are everywhere, and more are coming online every day. You need a way to analyze all of the data coming from your devices, but it can be expensive to transmit all of the data from a sensor to your central analytics engine.
-Apache Quarks is an open source programming model and runtime for edge devices that enables you to analyze data and events at the device. When you analyze on the edge, you can:
+Apache Edgent is an open source programming model and runtime for edge devices that enables you to analyze data and events at the device. When you analyze on the edge, you can:
* Reduce the amount of data that you transmit to your analytics server
* Reduce the amount of data that you store
-A Quarks application uses analytics to determine when data needs to be sent to a back-end system for further analysis, action, or storage. For example, you can use Quarks to determine whether a system is running outside of normal parameters, such as an engine that is running too hot.
+An Edgent application uses analytics to determine when data needs to be sent to a back-end system for further analysis, action, or storage. For example, you can use Edgent to determine whether a system is running outside of normal parameters, such as an engine that is running too hot.
-If the system is running normally, you don\u2019t need to send this data to your back-end system; it\u2019s an added cost and an additional load on your system to process and store. However, if Quarks detects an issue, you can transmit that data to your back-end system to determine why the issue is occurring and how to resolve the issue.
+If the system is running normally, you don\u2019t need to send this data to your back-end system; it\u2019s an added cost and an additional load on your system to process and store. However, if Edgent detects an issue, you can transmit that data to your back-end system to determine why the issue is occurring and how to resolve the issue.
-Quarks enables you to shift from sending a continuous flow of trivial data to the server to sending only essential and meaningful data as it occurs. This is especially important when the cost of communication is high, such as when using a cellular network to transmit data, or when bandwidth is limited.
+Edgent enables you to shift from sending a continuous flow of trivial data to the server to sending only essential and meaningful data as it occurs. This is especially important when the cost of communication is high, such as when using a cellular network to transmit data, or when bandwidth is limited.
-The following use cases describe the primary situations in which you would use Quarks:
+The following use cases describe the primary situations in which you would use Edgent:
* *Internet of Things (IoT):* Analyze data on distributed edge devices and mobile devices to:
* Reduce the cost of transmitting data
@@ -33,7 +33,7 @@ The following environments have been tested for deployment on edge devices:
* Android
## Edge devices and back-end systems
-You can send data from a Quarks application to your back-end system when you need to perform analysis that cannot be performed on the edge device, such as:
+You can send data from an Edgent application to your back-end system when you need to perform analysis that cannot be performed on the edge device, such as:
* Running a complex analytic algorithm that requires more resources, such as CPU or memory, than are available on the edge device.
* Maintaining large amounts of state information about a device, such as several hours worth of state information for a patient\u2019s
@@ -44,7 +44,7 @@ medical device.
* Data of record, such as a patient\u2019s medical history or trucking manifests
* Data from other devices
-Quarks communicates with your back-end systems through the following message hubs:
+Edgent communicates with your back-end systems through the following message hubs:
* MQTT \u2013 The messaging standard for IoT
* IBM Watson IoT Platform \u2013 A cloud-based service that provides a device model on top of MQTT
http://git-wip-us.apache.org/repos/asf/incubator-quarks-website/blob/05ad5e88/site/docs/quarks-getting-started.md
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diff --git a/site/docs/quarks-getting-started.md b/site/docs/quarks-getting-started.md
deleted file mode 100644
index 64f58e6..0000000
--- a/site/docs/quarks-getting-started.md
+++ /dev/null
@@ -1,197 +0,0 @@
----
-title: Getting started with Apache Quarks
----
-
-## What is Apache Quarks?
-
-Quarks is an open source programming model and runtime for edge devices that enables you to analyze streaming data on your edge devices. When you analyze on the edge, you can:
-
-* Reduce the amount of data that you transmit to your analytics server
-* Reduce the amount of data that you store
-
-For more information, see the [Quarks overview](home).
-
-### Apache Quarks and streaming analytics
-
-The fundamental building block of a Quarks application is a **stream**: a continuous sequence of tuples (messages, events, sensor readings, and so on).
-
-The Quarks API provides the ability to process or analyze each tuple as it appears on a stream, resulting in a derived stream.
-
-Source streams are streams that originate data for analysis, such as readings from a device's temperature sensor.
-
-Streams are terminated using sink functions that can perform local device control or send information to centralized analytic systems through a message hub.
-
-Quarks' primary API is functional where streams are sourced, transformed, analyzed or sinked though functions, typically represented as lambda expressions, such as `reading -> reading < 50 || reading > 80` to filter temperature readings in Fahrenheit.
-
-### Downloading Apache Quarks
-
-To use Quarks, access the source code and build it. You can read more about building Quarks [here](https://github.com/apache/incubator-quarks/blob/master/DEVELOPMENT.md).
-
-After you build the Quarks package, you can set up your environment.
-
-### Setting up your environment
-
-Ensure that you are running a supported environment. For more information, see the [Quarks overview](home). This guide assumes you're running Java 8.
-
-The Quarks Java 8 JAR files are located in the `quarks/java8/lib` directory.
-
-1. Create a new Java project in Eclipse, and specify Java 8 as the execution environment JRE:
-
- <img src="images/New_Java_Project.JPG" style="width:462px;height:582px;">
-
-
-2. Modify the Java build path to include all of the JAR files in the `quarks\java8\lib` directory:
-
- <img src="images/Build_Path_Jars.JPG" style="width:661px;height:444px;">
-
-Your environment is set up! You can start writing your first Quarks application.
-
-## Creating a simple application
-
-If you're new to Quarks or to writing streaming applications, the best way to get started is to write a simple program.
-
-Quarks is a framework that pushes data analytics and machine learning to *edge devices*. (Edge devices include things like routers, gateways, machines, equipment, sensors, appliances, or vehicles that are connected to a network.) Quarks enables you to process data locally—such as, in a car engine, on an Android phone, or Raspberry Pi—before you send data over a network.
-
-For example, if your device takes temperature readings from a sensor 1,000 times per second, it is more efficient to process the data locally and send only interesting or unexpected results over the network. To simulate this, let's define a (simulated) TempSensor class:
-
-```java
-import java.util.Random;
-
-import quarks.function.Supplier;
-
-/**
- * Every time get() is called, TempSensor generates a temperature reading.
- */
-public class TempSensor implements Supplier<Double> {
- double currentTemp = 65.0;
- Random rand;
-
- TempSensor(){
- rand = new Random();
- }
-
- @Override
- public Double get() {
- // Change the current temperature some random amount
- double newTemp = rand.nextGaussian() + currentTemp;
- currentTemp = newTemp;
- return currentTemp;
- }
-}
-```
-
-Every time you call `TempSensor.get()`, it returns a new temperature reading. The continuous temperature readings are a stream of data that a Quarks application can process.
-
-Our sample Quarks application processes this stream by filtering the data and printing the results. Let's define a TempSensorApplication class for the application:
-
-```java
-import java.util.concurrent.TimeUnit;
-
-import quarks.providers.direct.DirectProvider;
-import quarks.topology.TStream;
-import quarks.topology.Topology;
-
-public class TempSensorApplication {
- public static void main(String[] args) throws Exception {
- TempSensor sensor = new TempSensor();
- DirectProvider dp = new DirectProvider();
- Topology topology = dp.newTopology();
- TStream<Double> tempReadings = topology.poll(sensor, 1, TimeUnit.MILLISECONDS);
- TStream<Double> filteredReadings = tempReadings.filter(reading -> reading < 50 || reading > 80);
-
- filteredReadings.print();
- dp.submit(topology);
- }
-}
-```
-
-To understand how the application processes the stream, let's review each line.
-
-### Specifying a provider
-
-Your first step when you write a Quarks application is to create a [`DirectProvider`]({{ site.docsurl }}/lastest/index.html?quarks/providers/direct/DirectProvider.html):
-
-```java
-DirectProvider dp = new DirectProvider();
-```
-
-A `Provider` is an object that contains information on how and where your Quarks application will run. A `DirectProvider` is a type of Provider that runs your application directly within the current virtual machine when its `submit()` method is called.
-
-### Creating a topology
-
-Additionally a Provider is used to create a [`Topology`]({{ site.docsurl }}/lastest/index.html?quarks/topology/Topology.html) instance:
-
-```java
-Topology topology = dp.newTopology();
-```
-
-In Quarks, `Topology` is a container that describes the structure of your application:
-
-* Where the streams in the application come from
-* How the data in the stream is modified
-
-In the TempSensor application above, we have exactly one data source: the `TempSensor` object. We define the source stream by calling `topology.poll()`, which takes both a `Supplier` function and a time parameter to indicate how frequently readings should be taken. In our case, we read from the sensor every millisecond:
-
-```java
-TStream<Double> tempReadings = topology.poll(sensor, 1, TimeUnit.MILLISECONDS);
-```
-
-### Defining the `TStream` object
-
-Calling `topology.poll()` to define a source stream creates a `TStream<Double>` instance, which represents the series of readings taken from the temperature sensor.
-
-A streaming application can run indefinitely, so the `TStream` might see an arbitrarily large number of readings pass through it. Because a `TStream` represents the flow of your data, it supports a number of operations which allow you to modify your data.
-
-### Filtering a `TStream`
-
-In our example, we want to filter the stream of temperature readings, and remove any "uninteresting" or expected readings—specifically readings which are above 50 degrees and below 80 degrees. To do this, we call the `TStream`'s `filter` method and pass in a function that returns *true* if the data is interesting and *false* if the data is uninteresting:
-
-```java
-TStream<Double> filteredReadings = tempReadings.filter(reading -> reading < 50 || reading > 80);
-```
-
-As you can see, the function that is passed to `filter` operates on each tuple individually. Unlike data streaming frameworks like [Apache Spark](https://spark.apache.org/), which operate on a collection of data in batch mode, Quarks achieves low latency processing by manipulating each piece of data as soon as it becomes available. Filtering a `TStream` produces another `TStream` that contains only the filtered tuples; for example, the `filteredReadings` stream.
-
-### Printing to output
-
-When our application detects interesting data (data outside of the expected parameters), we want to print results. You can do this by calling the `TStream.print()` method, which prints using `.toString()` on each tuple that passes through the stream:
-
-```java
-filteredReadings.print();
-```
-
-Unlike `TStream.filter()`, `TStream.print()` does not produce another `TStream`. This is because `TStream.print()` is a **sink**, which represents the terminus of a stream.
-
-In addition to `TStream.print()` there are other sink operations that send tuples to an MQTT server, JDBC connection, file, or Kafka cluster. Additionally, you can define your own sink by invoking `TStream.sink()` and passing in your own function.
-
-### Submitting your application
-
-Now that your application has been completely declared, the final step is to run your application.
-
-`DirectProvider` contains a `submit()` method, which runs your application directly within the current virtual machine:
-
-```java
-dp.submit(topology);
-```
-
-After you run your program, you should see output containing only "interesting" data coming from your sensor:
-
-```
-49.904032311772596
-47.97837504039084
-46.59272336309031
-46.681544551652934
-47.400819234155236
-...
-```
-
-As you can see, all temperatures are outside the 50-80 degree range. In terms of a real-world application, this would prevent a device from sending superfluous data over a network, thereby reducing communication costs.
-
-## Further examples
-
-This example demonstrates a small piece of Quarks' functionality. Quarks supports more complicated topologies, such as topologies that require merging and splitting data streams, or perform operations which aggregate the last *N* seconds of data (for example, calculating a moving average).
-
-For more complex examples, see:
-
-* [Quarks sample programs](samples)
-* [Common Quarks operations](common-quarks-operations)
http://git-wip-us.apache.org/repos/asf/incubator-quarks-website/blob/05ad5e88/site/docs/quarks_index.md
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--- a/site/docs/quarks_index.md
+++ /dev/null
@@ -1,29 +0,0 @@
----
-title: Apache Quarks documentation
-audience: field engineers, clients
----
-
-## New documentation
-
-Apache Quarks is evolving, and so is the documentation. If the existing documentation hasn't answered your questions, you can request new or updated documentation by opening a [Jira](https://issues.apache.org/jira/browse/QUARKS) issue.
-
-## Providing feedback
-
-To provide feedback on our documentation:
-
-1. Navigate to the documentation page for which you are providing feedback
-1. Click on the **Feedback** button in the top right corner
-
-This will open an issue for the page that you are currently visiting.
-
-## Contributing documentation
-
-If you have ideas on how we can better document or explain some of the concepts, we would love to have your contribution! This site uses GitHub's flavor of Markdown and Jekyll markdown for our documentation.
-
-Refer to this documentation on GitHub's flavor of Markdown: [Writing on GitHub](https://help.github.com/categories/writing-on-github).
-
-Refer to this documentation to get started: [Using Jekyll with Pages](https://help.github.com/articles/using-jekyll-with-pages/).
-
-To contribute, clone this project locally, make your changes, and create a [pull request](https://github.com/apache/incubator-quarks-website/pulls).
-
-To learn more, visit [Get Involved](getinvolved).
http://git-wip-us.apache.org/repos/asf/incubator-quarks-website/blob/05ad5e88/site/docs/quickstart.md
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diff --git a/site/docs/quickstart.md b/site/docs/quickstart.md
index e8f049c..5ea19e3 100644
--- a/site/docs/quickstart.md
+++ b/site/docs/quickstart.md
@@ -2,16 +2,16 @@
title: Quickstart IBM Watson IoT Platform sample
---
-## Quarks to Quickstart quickly!
+## Edgent to Quickstart quickly!
-IoT devices running quarks applications typically connect to back-end analytic systems through a message hub. Message hubs are used to isolate the back-end system from having to handle connections from thousands to millions of devices.
+IoT devices running Edgent applications typically connect to back-end analytic systems through a message hub. Message hubs are used to isolate the back-end system from having to handle connections from thousands to millions of devices.
An example of such a message hub designed for the Internet of Things is [IBM Watson IoT Platform](https://internetofthings.ibmcloud.com/). This cloud service runs on IBM's Bluemix cloud platform
-and Quarks provides a [connector]({{ site.docsurl }}/lastest/index.html?quarks/connectors/iotf/IotfDevice.html).
+and Edgent provides a [connector]({{ site.docsurl }}/latest/index.html?{{ site.data.project.unix_name }}/connectors/iotf/IotfDevice.html).
-You can test out the service without any registration by using its Quickstart service and the Quarks sample application: [code](https://github.com/apache/incubator-quarks/blob/master/samples/connectors/src/main/java/quarks/samples/connectors/iotf/IotfQuickstart.java), [JavaDocs]({{ site.docsurl }}/lastest/index.html?quarks/samples/connectors/iotf/IotfQuickstart.html).
+You can test out the service without any registration by using its Quickstart service and the Edgent sample application: [code]({{ site.data.project.source_repository_mirror }}/blob/master/samples/connectors/src/main/java/{{ site.data.project.unix_name }}/samples/connectors/iotf/IotfQuickstart.java), [Javadoc]({{ site.docsurl }}/latest/index.html?{{ site.data.project.unix_name }}/samples/connectors/iotf/IotfQuickstart.html).
-You can execute the class directly from Eclipse, or using the script: [`quarks/java8/scripts/connectors/iotf/runiotfquickstart.sh`](https://github.com/quarks-edge/quarks/blob/master/scripts/connectors/iotf/runiotfquickstart.sh)
+You can execute the class directly from Eclipse, or using the script: [`edgent/java8/scripts/connectors/iotf/runiotfquickstart.sh`]({{ site.data.project.source_repository_mirror }}/blob/master/scripts/connectors/iotf/runiotfquickstart.sh)
When run it produces output like this, with a URL as the third line.
@@ -23,9 +23,9 @@ Here's an example view:
<img border="0" alt="Quickstart service output" src="images/Quickstart.png">
-## Quarks code
+## Edgent code
-The full source is at: [IotfQuickstart.java](https://github.com/apache/incubator-quarks/blob/master/samples/connectors/src/main/java/quarks/samples/connectors/iotf/IotfQuickstart.java).
+The full source is at: [IotfQuickstart.java]({{ site.data.project.source_repository_mirror }}/blob/master/samples/connectors/src/main/java/{{ site.data.project.unix_name }}/samples/connectors/iotf/IotfQuickstart.java).
The first step to is to create a `IotDevice` instance that represents the connection to IBM Watson IoT Platform Quickstart service.
@@ -53,4 +53,4 @@ Now we have a stream of simulated sensor reading events as JSON tuples (`json`)
device.events(json, "sensors", QoS.FIRE_AND_FORGET);
```
-It's that simple to send tuples on a Quarks stream to IBM Watson IoT Platform as device events.
+It's that simple to send tuples on an Edgent stream to IBM Watson IoT Platform as device events.
http://git-wip-us.apache.org/repos/asf/incubator-quarks-website/blob/05ad5e88/site/docs/samples.md
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diff --git a/site/docs/samples.md b/site/docs/samples.md
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+++ b/site/docs/samples.md
@@ -2,33 +2,33 @@
title: Sample programs
---
-The [Getting started guide](quarks-getting-started) includes a step-by-step walkthrough of a simple Quarks application.
+The [Getting started guide](edgent-getting-started) includes a step-by-step walkthrough of a simple Edgent application.
-Quarks also includes a number of sample Java applications that demonstrate different ways that you can use and implement Quarks.
+Edgent also includes a number of sample Java applications that demonstrate different ways that you can use and implement Edgent.
-If you are using a released version of Quarks, the samples are already compiled and ready to use. If you downloaded the source or the Git project, the samples are built when you build Quarks.
+If you are using a released version of Edgent, the samples are already compiled and ready to use. If you downloaded the source or the Git project, the samples are built when you build Edgent.
## Resources
-The samples are currently available only for Java 8 environments. To use the samples, you'll need the resources in the following subdirectories of the Quarks package.:
+The samples are currently available only for Java 8 environments. To use the samples, you'll need the resources in the following subdirectories of the Edgent package.:
* The `java8/samples` directory contains the Java code for the samples
* The `java8/scripts` directory contains the shell scripts that you need to run the samples
-If you use any of the samples in your own applications, ensure that you include the related Quarks JAR files in your `classpath`.
+If you use any of the samples in your own applications, ensure that you include the related Edgent JAR files in your `classpath`.
## Recommended samples
-In addition to the sample application in the [Getting started guide](quarks-getting-started), the following samples can help you start developing with Quarks:
+In addition to the sample application in the [Getting started guide](edgent-getting-started), the following samples can help you start developing with Edgent:
-* **HelloQuarks**
+* **HelloEdgent**
- This simple program demonstrates the basic mechanics of declaring and executing a topology
* **PeriodicSource**
- This simple program demonstrates how to periodically poll a source for data to create a source stream
* **SimpleFilterTransform**
- This simple program demonstrates a simple analytics pipeline: `source -> filter -> transform -> sink`
* **SensorAnalytics**
- - This more complex program demonstrates multiple facets of a Quarks application, including:
+ - This more complex program demonstrates multiple facets of an Edgent application, including:
* Configuration control
* Reading data from a device with multiple sensors
* Running common analytic algorithms
@@ -37,7 +37,7 @@ In addition to the sample application in the [Getting started guide](quarks-gett
* Logging results locally
* Conditional stream tracing
* **IBM Watson IoT Platform**
- - Samples that demonstrate how to use IBM Watson IoT Platform as the IoT scale message hub between Quarks and back-end analytic systems:
+ - Samples that demonstrate how to use IBM Watson IoT Platform as the IoT scale message hub between Edgent and back-end analytic systems:
* [Sample using the no-registration Quickstart service](quickstart)
-Additional samples are documented in the [Quarks Overview]({{ site.docsurl }}/lastest/overview-summary.html#overview.description) section of the Javadoc.
+Additional samples are documented in the [Edgent Overview]({{ site.docsurl }}/latest/overview-summary.html#overview.description) section of the Javadoc.
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--- a/site/index.html
+++ b/site/index.html
@@ -1,6 +1,6 @@
---
layout: default_orig
-title: Quarks
+title: Edgent
subTitle: A Community for <br>Accelerating Analytics at the Edge
---
<!--
http://git-wip-us.apache.org/repos/asf/incubator-quarks-website/blob/05ad5e88/site/javadoc/lastest/allclasses-frame.html
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+++ /dev/null
@@ -1,254 +0,0 @@
-<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
-<!-- NewPage -->
-<html lang="en">
-<head>
-<!-- Generated by javadoc (1.8.0_71) on Tue May 17 00:28:47 UTC 2016 -->
-<title>All Classes (Quarks v0.4.0)</title>
-<meta name="date" content="2016-05-17">
-<link rel="stylesheet" type="text/css" href="stylesheet.css" title="Style">
-<script type="text/javascript" src="script.js"></script>
-</head>
-<body>
-<h1 class="bar">All Classes</h1>
-<div class="indexContainer">
-<ul>
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-<li><a href="quarks/test/svt/apps/iotf/AbstractIotfApplication.html" title="class in quarks.test.svt.apps.iotf" target="classFrame">AbstractIotfApplication</a></li>
-<li><a href="quarks/samples/apps/mqtt/AbstractMqttApplication.html" title="class in quarks.samples.apps.mqtt" target="classFrame">AbstractMqttApplication</a></li>
-<li><a href="quarks/oplet/core/AbstractOplet.html" title="class in quarks.oplet.core" target="classFrame">AbstractOplet</a></li>
-<li><a href="quarks/oplet/window/Aggregate.html" title="class in quarks.oplet.window" target="classFrame">Aggregate</a></li>
-<li><a href="quarks/topology/services/ApplicationService.html" title="interface in quarks.topology.services" target="classFrame"><span class="interfaceName">ApplicationService</span></a></li>
-<li><a href="quarks/topology/mbeans/ApplicationServiceMXBean.html" title="interface in quarks.topology.mbeans" target="classFrame"><span class="interfaceName">ApplicationServiceMXBean</span></a></li>
-<li><a href="quarks/samples/apps/ApplicationUtilities.html" title="class in quarks.samples.apps" target="classFrame">ApplicationUtilities</a></li>
-<li><a href="quarks/runtime/appservice/AppService.html" title="class in quarks.runtime.appservice" target="classFrame">AppService</a></li>
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