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From u..@apache.org
Subject [14/30] flink git commit: [docs] Change doc layout
Date Wed, 22 Apr 2015 14:17:11 GMT
http://git-wip-us.apache.org/repos/asf/flink/blob/f1ee90cc/docs/img/state_machine.svg
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diff --git a/docs/img/state_machine.svg b/docs/img/state_machine.svg
deleted file mode 100644
index 8d0f570..0000000
--- a/docs/img/state_machine.svg
+++ /dev/null
@@ -1,318 +0,0 @@
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http://git-wip-us.apache.org/repos/asf/flink/blob/f1ee90cc/docs/index.md
----------------------------------------------------------------------
diff --git a/docs/index.md b/docs/index.md
index 7cac789..d218cc7 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -1,5 +1,5 @@
 ---
-title: Flink Overview
+title: "Overview"
 ---
 <!--
 Licensed to the Apache Software Foundation (ASF) under one
@@ -18,7 +18,7 @@ software distributed under the License is distributed on an
 KIND, either express or implied.  See the License for the
 specific language governing permissions and limitations
 under the License.
---> 
+-->
 
 Apache Flink is a platform for efficient, distributed, general-purpose data processing.
 It features powerful programming abstractions in Java and Scala, a high-performance runtime, and
@@ -33,32 +33,32 @@ a thorough introduction of the Flink API please refer to the
 
 This is an overview of Flink's stack. Click on any component to go to the respective documentation.
 
-<img src="img/overview-stack-0.9.png" width="893" height="450" alt="Stack" usemap="#overview-stack">
+<img src="fig/overview-stack-0.9.png" width="893" height="450" alt="Stack" usemap="#overview-stack">
 
 <map name="overview-stack">
-  <area shape="rect" coords="188,0,263,200" alt="Graph API: Gelly" href="gelly_guide.html">
-  <!-- <area shape="rect" coords="268,0,343,200" alt="Flink ML" href="ml.htm"> -->
-  <area shape="rect" coords="348,0,423,200" alt="Table" href="table.html">
+  <area shape="rect" coords="188,0,263,200" alt="Graph API: Gelly" href="libs/gelly_guide.html">
+  <area shape="rect" coords="268,0,343,200" alt="Flink ML" href="libs/ml/">
+  <area shape="rect" coords="348,0,423,200" alt="Table" href="libs/table.html">
 
-  <area shape="rect" coords="188,205,538,260" alt="DataSet API (Java/Scala)" href="programming_guide.html">
-  <area shape="rect" coords="543,205,893,260" alt="DataStream API (Java/Scala)" href="streaming_guide.html">
+  <area shape="rect" coords="188,205,538,260" alt="DataSet API (Java/Scala)" href="apis/programming_guide.html">
+  <area shape="rect" coords="543,205,893,260" alt="DataStream API (Java/Scala)" href="apis/streaming_guide.html">
 
-  <area shape="rect" coords="188,275,538,330" alt="Optimizer" href="optimizer.html">
+  <!-- <area shape="rect" coords="188,275,538,330" alt="Optimizer" href="optimizer.html"> -->
   <!-- <area shape="rect" coords="543,275,893,330" alt="Stream Builder" href="streambuilder.html"> -->
 
-  <area shape="rect" coords="188,335,893,385" alt="Flink Runtime" href="internal_general_arch.html">
+  <area shape="rect" coords="188,335,893,385" alt="Flink Runtime" href="internals/general_arch.html">
 
-  <area shape="rect" coords="188,405,328,455" alt="Local" href="local_execution.html">
-  <area shape="rect" coords="333,405,473,455" alt="Remote" href="cluster_execution.html">
-  <area shape="rect" coords="478,405,638,455" alt="Embedded" href="local_execution.html">
-  <area shape="rect" coords="643,405,765,455" alt="YARN" href="yarn_setup.html">
-  <area shape="rect" coords="770,405,893,455" alt="Tez" href="flink_on_tez_guide.html">
+  <area shape="rect" coords="188,405,328,455" alt="Local" href="apis/local_execution.html">
+  <area shape="rect" coords="333,405,473,455" alt="Remote" href="apis/cluster_execution.html">
+  <area shape="rect" coords="478,405,638,455" alt="Embedded" href="apis/local_execution.html">
+  <area shape="rect" coords="643,405,765,455" alt="YARN" href="setup/yarn_setup.html">
+  <area shape="rect" coords="770,405,893,455" alt="Tez" href="setup/flink_on_tez.html">
 </map>
 
 ## Download
 
-This documentation is for the next upcoming major release version {{ site.FLINK_VERSION_THIS_SHORT }} of Apache Flink.
+This documentation is for Apache Flink version {{ site.version }}, which is the current development version of the next upcoming major release of Apache Flink.
 
-You can download the latest pre-built snapshot version from the [downloads]({{ site.FLINK_DOWNLOAD_URL }}#latest) page of the [project website]({{ site.FLINK_WEBSITE_URL }}).
+You can download the latest pre-built snapshot version from the [downloads]({{ site.download_url }}#latest) page of the [project website]({{ site.website_url }}).
 
-The Scala API uses Scala {{ site.FLINK_SCALA_VERSION_SHORT }}. Please make sure to use a compatible version.
+The Scala API uses Scala {{ site.scala_version }}. Please make sure to use a compatible version.

http://git-wip-us.apache.org/repos/asf/flink/blob/f1ee90cc/docs/internal_add_operator.md
----------------------------------------------------------------------
diff --git a/docs/internal_add_operator.md b/docs/internal_add_operator.md
deleted file mode 100644
index c564221..0000000
--- a/docs/internal_add_operator.md
+++ /dev/null
@@ -1,251 +0,0 @@
----
-title:  "How to add a new Operator"
----
-<!--
-Licensed to the Apache Software Foundation (ASF) under one
-or more contributor license agreements.  See the NOTICE file
-distributed with this work for additional information
-regarding copyright ownership.  The ASF licenses this file
-to you under the Apache License, Version 2.0 (the
-"License"); you may not use this file except in compliance
-with the License.  You may obtain a copy of the License at
-
-  http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing,
-software distributed under the License is distributed on an
-"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-KIND, either express or implied.  See the License for the
-specific language governing permissions and limitations
-under the License.
--->
-
-* This will be replaced by the TOC
-{:toc}
-
-Operators in the Java API can be added in multiple different ways: 
-
-1. On the DataSet, as a specialization/combination of existing operators
-2. As a custom extension operator
-3. As a new runtime operator
-
-The first two approaches are typically more lightweight and easier to implement. Sometimes,
-new functionality does require a new runtime operator, or it is much more efficient to 
-
-
-## Implementing a new Operator on DataSet
-
-Many operators can be implemented as a specialization of another operator, or by means of a UDF.
-
-The simplest example are the `sum()`, `min()`, and `max()` functions on the
-{% gh_link /flink-java/src/main/java/org/apache/flink/api/java/DataSet.java "DataSet" %}.
-These functions simply call other operations with some pre-defined parameters:
-
-~~~java
-public AggregateOperator<T> sum (int field) {
-    return this.aggregate (Aggregations.SUM, field);
-}
-
-~~~
-
-Some operations can be implemented as compositions of multiple other operators. An example is to implement a
-*count()* function through a combination of *map* and *aggregate*. 
-
-A simple way to do this is to define a function on the {% gh_link /flink-java/src/main/java/org/apache/flink/api/java/DataSet.java "DataSet" %} that calls *map(...)* and *reduce(...)* in turn:
-
-~~~java
-public DataSet<Long> count() {
-    return this.map(new MapFunction<T, Long>() {
-                        public Long map(T value) {
-                            return 1L;
-                        }
-                    })
-               .reduce(new ReduceFunction<Long>() {
-                        public Long reduce(Long val1, Long val1) {
-                            return val1 + val2;
-                        }
-                    });
-}
-~~~
-
-To define a new operator without altering the DataSet class is possible by putting the functions as static members
-into another class. The example of the *count()* operator would look the following way:
-
-~~~java
-public static <T>DataSet<Long> count(DataSet<T> data) {
-    return data.map(...).reduce(...);
-}
-~~~
-
-### More Complex Operators
-
-A more complex example of an operation via specialization is the {% gh_link /flink-java/src/main/java/org/apache/flink/api/java/operators/AggregateOperator.java "Aggregation Operation" %} in the Java API. It is implemented by means of a *GroupReduce* UDF.
-
-The Aggregate Operation comes with its own operator in the *Java API*, but translates itself into a {% gh_link /flink-core/src/main/java/org/apache/flink/api/common/operators/base/GroupReduceOperatorBase.java "GroupReduceOperatorBase" %} in the *Common API*. (see [Program Life Cycle](internal_program_life_cycle.html) for details of how an operation from the *Java API* becomes an operation of the *Common API* and finally a runtime operation.)
-The Java API aggregation operator is only a builder that takes the types of aggregations and the field positions, and used that information to
-parameterize the GroupReduce UDF that performs the aggregations.
-
-Because the operation is translated into a GroupReduce operation, it appears as a GroupReduceOperator in the optimizer and runtime.
-
-
-
-## Implementing a Custom Extension Operator
-
-The DataSet offers a method for custom operators: `DataSet<X> runOperation(CustomUnaryOperation<T, X> operation)`.
-The *CustomUnaryOperation* interface defines operators by means of the two functions:
-
-~~~ java
-void setInput(DataSet<IN> inputData);
-	
-DataSet<OUT> createResult();
-~~~
-
-The {% gh_link /flink-staging/flink-spargel/src/main/java/org/apache/flink/spargel/java/VertexCentricIteration.java "VertexCentricIteration" %} operator is implemented that way. Below is an example how to implement the *count()* operator that way.
-
-~~~ java
-public class Counter<T> implements CustomUnaryOperation<T, Long> {
-
-    private DataSet<T> input;
-
-    public void setInput(DataSet<IN> inputData) { this.input = inputData; }
-
-    public DataSet<Long> createResult() {
-        return input.map(...).reduce(...);
-    }
-}
-~~~
-
-The CountOperator can be called in the following way:
-
-~~~ java
-DataSet<String> lines = ...;
-DataSet<Long> count = lines.runOperation(new Counter<String>());
-~~~
-
-
-## Implementing a new Runtime Operator
-
-Adding an new runtime operator requires changes throughout the entire stack, from the API to the runtime:
-
-- *Java API*
-- *Common API*
-- *Optimizer*
-- *Runtime*
-
-We start the description bottom up, at the example of the *mapPartition()* function, which is like a *map*
-function, but invoked only once per parallel partition.
-
-**Runtime**
-
-Runtime Operators are implemented using the {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/operators/PactDriver.java "Driver" %} interface. The interface defines the methods that describe the operator towards the runtime. The {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/operators/MapDriver.java "MapDriver" %} serves as a simple example of how those operators work.
-
-The runtime works with the `MutableObjectIterator`, which describes data streams with the ability to reuse objects, to reduce pressure on the garbage collector.
-
-An implementation of the central `run()` method for the *mapPartition* operator could look the following way:
-
-~~~ java
-public void run() throws Exception {
-    final MutableObjectIterator<IN> input = this.taskContext.getInput(0);
-    final MapPartitionFunction<IN, OUT> function = this.taskContext.getStub();
-    final Collector<OUT> output = this.taskContext.getOutputCollector();
-    final TypeSerializer<IN> serializer = this.taskContext.getInputSerializer(0);
-
-    // we assume that the UDF takes a java.util.Iterator, so we wrap the MutableObjectIterator
-    Iterator<IN> iterator = new MutableToRegularIteratorWrapper(input, serializer);
-
-    function.mapPartition(iterator, output);
-}
-~~~
-
-To increase efficiency, it is often beneficial to implement a *chained* version of an operator. Chained
-operators run in the same thread as their preceding operator, and work with nested function calls.
-This is very efficient, because it saves serialization/deserialization overhead.
-
-To learn how to implement a chained operator, take a look at the {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/operators/MapDriver.java "MapDriver" %} (regular) and the
-{% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/operators/chaining/ChainedMapDriver.java "ChainedMapDriver" %} (chained variant).
-
-
-### Optimizer/Compiler
-
-This section does a minimal discussion of the important steps to add an operator. Please see the [Optimizer](internal_optimizer.html) docs for more detail on how the optimizer works.
-To allow the optimizer to include a new operator in its planning, it needs a bit of information about it; in particular, the following information:
-
-- *{% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/operators/DriverStrategy.java "DriverStrategy" %}*: The operation needs to be added to the Enum, to make it available to the optimizer. The parameters to the Enum entry define which class implements the runtime operator, its chained version, whether the operator accumulates records (and needs memory for that), and whether it requires a comparator (works on keys). For our example, we can add the entry
-~~~ java
-MAP_PARTITION(MapPartitionDriver.class, null /* or chained variant */, PIPELINED, false)
-~~~
-
-- *Cost function*: The class {% gh_link /flink-compiler/src/main/java/org/apache/flink/compiler/costs/CostEstimator.java "CostEstimator" %} needs to know how expensive the operation is to the system. The costs here refer to the non-UDF part of the operator. Since the operator does essentially no work (it forwards the record stream to the UDF), the costs are zero. We change the `costOperator(...)` method by adding the *MAP_PARTITION* constant to the switch statement similar to the *MAP* constant such that no cost is accounted for it.
-
-- *OperatorDescriptor*: The operator descriptors define how an operation needs to be treated by the optimizer. They describe how the operation requires the input data to be (e.g., sorted or partitioned) and that way allows the optimizer to optimize the data movement, sorting, grouping in a global fashion. They do that by describing which {% gh_link /flink-compiler/src/main/java/org/apache/flink/compiler/dataproperties/RequestedGlobalProperties.java "RequestedGlobalProperties" %} (partitioning, replication, etc) and which {% gh_link /flink-compiler/src/main/java/org/apache/flink/compiler/dataproperties/RequestedLocalProperties.java "RequestedLocalProperties" %} (sorting, grouping, uniqueness) the operator has, as well as how the operator affects the existing {% gh_link /flink-compiler/src/main/java/org/apache/flink/compiler/dataproperties/GlobalProperties.java "GlobalProperties" %} and {% gh_link /flink-compiler/src/main/java/org/apache/flink/compiler/dataproperties/LocalProperties.j
 ava "LocalProperties" %}. In addition, it defines a few utility methods, for example to instantiate an operator candidate.
-Since the *mapPartition()* function is very simple (no requirements on partitioning/grouping), the descriptor is very simple. Other operators have more complex requirements, for example the {% gh_link /flink-compiler/src/main/java/org/apache/flink/compiler/operators/GroupReduceProperties.java "GroupReduce" %}. Some operators, like *join* have multiple ways in which they can be executed and therefore have multiple descriptors ({% gh_link /flink-compiler/src/main/java/org/apache/flink/compiler/operators/HashJoinBuildFirstProperties.java "Hash Join 1" %}, {% gh_link /flink-compiler/src/main/java/org/apache/flink/compiler/operators/HashJoinBuildSecondProperties.java "Hash Join 2" %}, {% gh_link /flink-compiler/src/main/java/org/apache/flink/compiler/operators/SortMergeJoinDescriptor.java "SortMerge Join" %}).
-The code sample below explains (with comments) how to create a descriptor for the *MapPartitionOperator* 
-
-  ~~~ java
-    public DriverStrategy getStrategy() {
-        return MAP_PARTITION;
-    }
-
-    // Instantiate the operator with the strategy over the input given in the form of the Channel
-    public SingleInputPlanNode instantiate(Channel in, SingleInputNode node) {
-        return new SingleInputPlanNode(node, "MapPartition", in, MAP_PARTITION);
-    }
-
-    // The operation accepts data with default global properties (arbitrary distribution)
-    protected List<RequestedGlobalProperties> createPossibleGlobalProperties() {
-        return Collections.singletonList(new RequestedGlobalProperties());
-    }
-
-    // The operation can accept data with any local properties. No grouping/sorting is necessary
-    protected List<RequestedLocalProperties> createPossibleLocalProperties() {
-        return Collections.singletonList(new RequestedLocalProperties());
-    }
-
-    // the operation itself does not affect the existing global properties.
-    // The effect of the UDF's semantics// are evaluated separately (by interpreting the
-    // semantic assertions)
-    public GlobalProperties computeGlobalProperties(GlobalProperties gProps) {
-        return gProps;
-    }
-
-    // since the operation can mess up all order, grouping, uniqueness, we cannot make any statements
-    // about how local properties are preserved
-    public LocalProperties computeLocalProperties(LocalProperties lProps) {
-        return LocalProperties.EMPTY;
-    }
-  ~~~
-
-- *OptimizerNode*: The optimizer node is the place where all comes together. It creates the list of *OperatorDescriptors*, implements the result data set size estimation, and assigns a name to the operation. It is a relatively small class and can be more or less copied again from the {% gh_link /flink-compiler/src/main/java/org/apache/flink/compiler/dag/MapNode.java "MapNode" %}.
-
-
-### Common API
-
-To make the operation available to the higher-level APIs, it needs to be added to the Common API. The simplest way to do this is to add a
-base operator. Create a class `MapPartitionOperatorBase`, after the pattern of the {% gh_link /flink-core/src/main/java/org/apache/flink/api/common/operators/base/MapOperatorBase.java "MapOperatorBase" %}.
-
-In addition, the optimizer needs to know which OptimizerNode how to create an OptimizerNode from the OperatorBase. This happens in the class
-`GraphCreatingVisitor` in the {% gh_link /flink-compiler/src/main/java/org/apache/flink/compiler/PactCompiler.java "Optimizer" %}.
-
-*Note:* A pending idea is to allow to skip this step by unifying the OptimizerNode and the Common API operator. They essentially fulfill the
-same function. The Common API operator exists only in order for the `flink-java` and `flink-scala` packages to not have a dependency on the
-optimizer.
-
-
-### Java API
-
-Create a Java API operator that is constructed in the same way as the {% gh_link /flink-java/src/main/java/org/apache/flink/api/java/operators/MapOperator.java "MapOperator" %}. The core method is the `translateToDataFlow(...)` method, which creates the Common API operator for the Java API operator.
-
-The final step is to add a function to the `DataSet` class:
-
-~~~ java
-public <R> DataSet<R> mapPartition(MapPartitionFunction<T, R> function) {
-    return new MapPartitionOperator<T, R>(this, function);
-}
-~~~
-
----
-
-*This documentation is maintained by the contributors of the individual components.
-We kindly ask anyone that adds and changes components to eventually provide a patch
-or pull request that updates these documents as well.*
-

http://git-wip-us.apache.org/repos/asf/flink/blob/f1ee90cc/docs/internal_distributed_akka.md
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diff --git a/docs/internal_distributed_akka.md b/docs/internal_distributed_akka.md
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--- a/docs/internal_distributed_akka.md
+++ /dev/null
@@ -1,47 +0,0 @@
----
-title:  "Distributed Communication and Coordination via Akka"
----
-<!--
-Licensed to the Apache Software Foundation (ASF) under one
-or more contributor license agreements.  See the NOTICE file
-distributed with this work for additional information
-regarding copyright ownership.  The ASF licenses this file
-to you under the Apache License, Version 2.0 (the
-"License"); you may not use this file except in compliance
-with the License.  You may obtain a copy of the License at
-
-  http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing,
-software distributed under the License is distributed on an
-"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-KIND, either express or implied.  See the License for the
-specific language governing permissions and limitations
-under the License.
--->
-
-This page discusses the implementation of Flink's distributed communication
-via Akka (http://akka.io)
-
-
-## Actor Systems
-
-### JobManager
-
-### TaskManager
-
-### JobClient
-
-
-## Actors and Messages
-
-
-## Failure Detection
-
-
-
----
-
-*This documentation is maintained by the contributors of the individual components.
-We kindly ask anyone that adds and changes components to eventually provide a patch
-or pull request that updates these documents as well.*

http://git-wip-us.apache.org/repos/asf/flink/blob/f1ee90cc/docs/internal_distributed_runtime.md
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diff --git a/docs/internal_distributed_runtime.md b/docs/internal_distributed_runtime.md
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index f6732d2..0000000
--- a/docs/internal_distributed_runtime.md
+++ /dev/null
@@ -1,23 +0,0 @@
----
-title:  "Distributed Runtime"
----
-<!--
-Licensed to the Apache Software Foundation (ASF) under one
-or more contributor license agreements.  See the NOTICE file
-distributed with this work for additional information
-regarding copyright ownership.  The ASF licenses this file
-to you under the Apache License, Version 2.0 (the
-"License"); you may not use this file except in compliance
-with the License.  You may obtain a copy of the License at
-
-  http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing,
-software distributed under the License is distributed on an
-"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-KIND, either express or implied.  See the License for the
-specific language governing permissions and limitations
-under the License.
--->
-
-Pending...

http://git-wip-us.apache.org/repos/asf/flink/blob/f1ee90cc/docs/internal_general_arch.md
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diff --git a/docs/internal_general_arch.md b/docs/internal_general_arch.md
deleted file mode 100644
index 2386a2e..0000000
--- a/docs/internal_general_arch.md
+++ /dev/null
@@ -1,89 +0,0 @@
----
-title:  "General Architecture and Process Model"
----
-<!--
-Licensed to the Apache Software Foundation (ASF) under one
-or more contributor license agreements.  See the NOTICE file
-distributed with this work for additional information
-regarding copyright ownership.  The ASF licenses this file
-to you under the Apache License, Version 2.0 (the
-"License"); you may not use this file except in compliance
-with the License.  You may obtain a copy of the License at
-
-  http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing,
-software distributed under the License is distributed on an
-"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-KIND, either express or implied.  See the License for the
-specific language governing permissions and limitations
-under the License.
--->
-
-* This will be replaced by the TOC
-{:toc}
-
-## The Processes
-
-When the Flink system is started, it bring up the *JobManager* and one or more *TaskManagers*. The JobManager
-is the coordinator of the Flink system, while the TaskManagers are the workers that execute parts of the
-parallel programs. When starting the system in *local* mode, a single JobManager and TaskManager are brought
-up within the same JVM.
-
-When a program is submitted, a client is created that performs the pre-processing and turns the program
-into the parallel data flow form that is executed by the JobManager and TaskManagers. The figure below
-illustrates the different actors in the system very coarsely.
-
-<div style="text-align: center;">
-<img src="img/ClientJmTm.svg" alt="The Interactions between Client, JobManager and TaskManager" height="400px" style="text-align: center;"/>
-</div>
-
-## Component Stack
-
-An alternative view on the system is given by the stack below. The different layers of the stack build on
-top of each other and raise the abstraction level of the program representations they accept:
-
-- The **runtime** layer receives a program in the form of a *JobGraph*. A JobGraph is a generic parallel
-data flow with arbitrary tasks that consume and produce data streams.
-
-- The **optimizer** and **common api** layer takes programs in the form of operator DAGs. The operators are
-specific (e.g., Map, Join, Filter, Reduce, ...), but are data type agnostic. The concrete types and their
-interaction with the runtime is specified by the higher layers.
-
-- The **API layer** implements multiple APIs that create operator DAGs for their programs. Each API needs
-to provide utilities (serializers, comparators) that describe the interaction between its data types and
-the runtime.
-
-<div style="text-align: center;">
-<img src="img/stack.svg" alt="The Flink component stack" width="800px" />
-</div>
-
-## Projects and Dependencies
-
-The Flink system code is divided into multiple sub-projects. The goal is to reduce the number of
-dependencies that a project implementing a Flink progam needs, as well as to faciltate easier testing
-of smaller sub-modules.
-
-The individual projects and their dependencies are shown in the figure below.
-
-<div style="text-align: center;">
-<img src="img/projects_dependencies.svg" alt="The Flink sub-projects and their dependencies" height="600px" style="text-align: center;"/>
-</div>
-
-In addition to the projects listed in the figure above, Flink currently contains the following sub-projects:
-
-- `flink-dist`: The *distribution* project. It defines how to assemble the compiled code, scripts, and other resources
-into the final folder structure that is ready to use.
-
-- `flink-staging`: A series of projects that are in an early version. Currently contains
-among other things projects for YARN support, JDBC data sources and sinks, hadoop compatibility,
-graph specific operators, and HBase connectors.
-
-- `flink-quickstart`: Scripts, maven archetypes, and example programs for the quickstarts and tutorials.
-
-- `flink-contrib`: Useful tools contributed by users. The code is maintained mainly by external contributors. The requirements for code being accepted into `flink-contrib` are lower compared to the rest of the code.
-
-
-
-
-

http://git-wip-us.apache.org/repos/asf/flink/blob/f1ee90cc/docs/internal_howto.md
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diff --git a/docs/internal_howto.md b/docs/internal_howto.md
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--- a/docs/internal_howto.md
+++ /dev/null
@@ -1,43 +0,0 @@
----
-title:  "Overview of Flink System Architecture & Internals"
----
-<!--
-Licensed to the Apache Software Foundation (ASF) under one
-or more contributor license agreements.  See the NOTICE file
-distributed with this work for additional information
-regarding copyright ownership.  The ASF licenses this file
-to you under the Apache License, Version 2.0 (the
-"License"); you may not use this file except in compliance
-with the License.  You may obtain a copy of the License at
-
-  http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing,
-software distributed under the License is distributed on an
-"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-KIND, either express or implied.  See the License for the
-specific language governing permissions and limitations
-under the License.
--->
-
-This documentation provides an overview of the "How-To's" for
-Flink developers. It is intended as guide to contributors and people
-that are interested in the technology behind Flink.
-
-
-## Architectures and Components
-
-- [How-to: Adding a new Operator](internal_add_operator.html)
-
-- [How-to: Using logging in Flink](internal_logging.html)
-
-- [How-to: Setting up Eclipse to develop Flink](internal_setup_eclipse.html)
-
-- [How-to: Setting up IntelliJ to develop Flink](internal_setup_intellij.html)
-
----
-
-*This documentation is maintained by the contributors of the individual components.
-We kindly ask anyone that adds and changes components to eventually provide a patch
-or pull request that updates these documents as well.*
-

http://git-wip-us.apache.org/repos/asf/flink/blob/f1ee90cc/docs/internal_job_scheduling.md
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diff --git a/docs/internal_job_scheduling.md b/docs/internal_job_scheduling.md
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index 2c55c01..0000000
--- a/docs/internal_job_scheduling.md
+++ /dev/null
@@ -1,82 +0,0 @@
----
-title:  "Jobs and Scheduling"
----
-<!--
-Licensed to the Apache Software Foundation (ASF) under one
-or more contributor license agreements.  See the NOTICE file
-distributed with this work for additional information
-regarding copyright ownership.  The ASF licenses this file
-to you under the Apache License, Version 2.0 (the
-"License"); you may not use this file except in compliance
-with the License.  You may obtain a copy of the License at
-
-  http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing,
-software distributed under the License is distributed on an
-"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-KIND, either express or implied.  See the License for the
-specific language governing permissions and limitations
-under the License.
--->
-
-This document briefly describes how Flink schedules jobs and 
-how it represents and tracks job status on the JobManager.
-
-* This will be replaced by the TOC
-{:toc}
-
-
-## Scheduling
-
-Execution resources in Flink are defined through _Task Slots_. Each TaskManager will have one or more task slots,
-each of which can run one pipeline of parallel tasks. A pipeline consists of multiple successive tasks, such as the
-*n-th* parallel instance of a MapFunction together with the *n-th* parallel instance of a ReduceFunction.
-Note that Flink often executes successive tasks concurrently: For Streaming programs, that happens in any case,
-but also for batch programs, it happens frequently.
-
-The figure below illustrates that. Consider a program with a data source, a *MapFunction*, and a *ReduceFunction*.
-The source and MapFunction are executed with a parallelism of 4, while the ReduceFunction is executed with a
-parallism of 3. A pipeline consists of the sequence Source - Map - Reduce. On a cluster with 2 TaskManagers with
-3 slots each, the program will be executed as described below.
-
-<div style="text-align: center;">
-<img src="img/slots.svg" alt="Assigning Pipelines of Tasks to Slots" height="250px" style="text-align: center;"/>
-</div>
-
-Internally, Flink defines through {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/jobmanager/scheduler/SlotSharingGroup.java "SlotSharingGroup" %} 
-and {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/jobmanager/scheduler/CoLocationGroup.java "CoLocationGroup" %}
-which tasks may share a slot (permissive), respectively which tasks must be strictly placed into the same slot.
-
-
-## JobManager Data Structures
-
-During job execution, the JobManager keeps track of distributed tasks, decides when to schedule the next task (or set of tasks),
-and reacts to finished tasks or execution failures.
-
-The JobManager receives the {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/jobgraph/ "JobGraph" %},
-which is a representation of the data flow consisting of operators ({% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/jobgraph/AbstractJobVertex.java "JobVertex" %})
-and intermediate results ({% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/jobgraph/IntermediateDataSet.java "IntermediateDataSet" %}).
-Each operator has properies, like the parallelism and the code that it executes.
-In addition, the JobGraph has a set of attached libraries, that are neccessary to execute the code of the operators.
-
-The JobManager transforms the JobGraph into an {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/ "ExecutionGraph" %}.
-The ExecutionGraph is a parallel version of the JobGraph: For each JobVertex, it contains an {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/ExecutionVertex.java "ExecutionVertex" %} per parallel subtask. An operator with a parallelism of 100 will have one JobVertex and 100 ExecutionVertices.
-The ExecutionVertex tracks the state of execution of a particular subtask. All ExecutionVertices from one JobVertex are held in an
-{% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/ExecutionJobVertex.java "ExecutionJobVertex" %},
-which tracks the status of the operator as a whole. 
-Besides the vertices, the ExecutionGraph also contains the {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/IntermediateResult.java "IntermediateResult" %} and the {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/IntermediateResultPartition.java "IntermediateResultPartition" %}. The former tracks the state of the *IntermediateDataSet*, the latter the state of each of its partitions.
-
-<div style="text-align: center;">
-<img src="img/job_and_execution_graph.svg" alt="JobGraph and ExecutionGraph" height="400px" style="text-align: center;"/>
-</div>
-
-During its execution, each parallel task goes through multiple stages, from *created* to *finished* or *failed*. The diagram below illustrates the 
-states and possible transitions between them. A task may be executed multiple times (for example in the course of failure recovery).
-For that reason, the execution of an ExecutionVertex is tracked in an {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/Execution.java "Execution" %}. Each ExecutionVertex has a current Execution, and prior Executions.
-
-<div style="text-align: center;">
-<img src="img/state_machine.svg" alt="States and Transitions of Task Executions" height="300px" style="text-align: center;"/>
-</div>
-
-

http://git-wip-us.apache.org/repos/asf/flink/blob/f1ee90cc/docs/internal_logging.md
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diff --git a/docs/internal_logging.md b/docs/internal_logging.md
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--- a/docs/internal_logging.md
+++ /dev/null
@@ -1,96 +0,0 @@
----
-title: "How to use logging"
----
-<!--
-Licensed to the Apache Software Foundation (ASF) under one
-or more contributor license agreements.  See the NOTICE file
-distributed with this work for additional information
-regarding copyright ownership.  The ASF licenses this file
-to you under the Apache License, Version 2.0 (the
-"License"); you may not use this file except in compliance
-with the License.  You may obtain a copy of the License at
-
-  http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing,
-software distributed under the License is distributed on an
-"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-KIND, either express or implied.  See the License for the
-specific language governing permissions and limitations
-under the License.
--->
-
-* This will be replaced by the TOC
-{:toc}
-
-The logging in Flink is implemented using the slf4j logging interface. As underlying logging framework, log4j is used. We also provide logback configuration files and pass them to the JVM's as properties. Users willing to use logback instead of log4j can just exclude log4j (or delete it from the lib/ folder).
-
-## Configuring Log4j
-
-Log4j is controlled using property files. In Flink's case, the file is usually called `log4j.properties`. We pass the filename and location of this file using the `-Dlog4j.configuration=` parameter to the JVM.
-
-## Configuring logback
-
-For users and developers alike it is important to control the logging framework. 
-The configuration of the logging framework is exclusively done by configuration files.
-The configuration file either has to be specified by setting the environment property `-Dlogback.configurationFile=<file>` or by putting `logback.xml` in the classpath.
-The `conf` directory contains a `logback.xml` file which can be modified and is used if Flink is started outside of an IDE and with the provided starting scripts.
-The provided `logback.xml` has the following form:
-
-~~~ xml
-<configuration>
-    <appender name="file" class="ch.qos.logback.core.FileAppender">
-        <file>${log.file}</file>
-        <append>false</append>
-        <encoder>
-            <pattern>%d{HH:mm:ss.SSS} [%thread] %-5level %logger{60} %X{sourceThread} - %msg%n</pattern>
-        </encoder>
-    </appender>
-
-    <root level="INFO">
-        <appender-ref ref="file"/>
-    </root>
-</configuration>
-~~~
-
-In order to control the logging level of `org.apache.flink.runtime.jobgraph.JobGraph`, for example, one would have to add the following line to the configuration file.
-
-~~~ xml
-<logger name="org.apache.flink.runtime.jobgraph.JobGraph" level="DEBUG"/>
-~~~
-
-For further information on configuring logback see [LOGback's manual](http://logback.qos.ch/manual/configuration.html).
-
-## Best practices for developers
-
-The loggers using slf4j are created by calling
-
-~~~ java
-import org.slf4j.LoggerFactory
-import org.slf4j.Logger
-
-Logger LOG = LoggerFactory.getLogger(Foobar.class)
-~~~
-
-In order to benefit most from slf4j, it is recommended to use its placeholder mechanism.
-Using placeholders allows to avoid unnecessary string constructions in case that the logging level is set so high that the message would not be logged.
-The syntax of placeholders is the following:
-
-~~~ java
-LOG.info("This message contains {} placeholders. {}", 2, "Yippie");
-~~~
-
-Placeholders can also be used in conjunction with exceptions which shall be logged.
-
-~~~ java
-catch(Exception exception){
-	LOG.error("An {} occurred.", "error", exception);
-}
-~~~
-
----
-
-*This documentation is maintained by the contributors of the individual components.
-We kindly ask anyone that adds and changes components to eventually provide a patch
-or pull request that updates these documents as well.*
-

http://git-wip-us.apache.org/repos/asf/flink/blob/f1ee90cc/docs/internal_operators_and_memory.md
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+++ /dev/null
@@ -1,21 +0,0 @@
----
-title:  "Runtime Algorithms and Memory Management"
----
-<!--
-Licensed to the Apache Software Foundation (ASF) under one
-or more contributor license agreements.  See the NOTICE file
-distributed with this work for additional information
-regarding copyright ownership.  The ASF licenses this file
-to you under the Apache License, Version 2.0 (the
-"License"); you may not use this file except in compliance
-with the License.  You may obtain a copy of the License at
-
-  http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing,
-software distributed under the License is distributed on an
-"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-KIND, either express or implied.  See the License for the
-specific language governing permissions and limitations
-under the License.
--->

http://git-wip-us.apache.org/repos/asf/flink/blob/f1ee90cc/docs/internal_optimizer.md
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diff --git a/docs/internal_optimizer.md b/docs/internal_optimizer.md
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--- a/docs/internal_optimizer.md
+++ /dev/null
@@ -1,21 +0,0 @@
----
-title:  "Optimizer"
----
-<!--
-Licensed to the Apache Software Foundation (ASF) under one
-or more contributor license agreements.  See the NOTICE file
-distributed with this work for additional information
-regarding copyright ownership.  The ASF licenses this file
-to you under the Apache License, Version 2.0 (the
-"License"); you may not use this file except in compliance
-with the License.  You may obtain a copy of the License at
-
-  http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing,
-software distributed under the License is distributed on an
-"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-KIND, either express or implied.  See the License for the
-specific language governing permissions and limitations
-under the License.
--->


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