Closes #1730

This closes #1714

* Explicitly state to stop the local environment

This closes #1718

- Move "Windowing" to separate page
  - Make "Working with Time" sub page of "Windowing"
  - Fix link in "Working with Time" page
- Move "Working with State" page to "Fault Tolerance"
  - Add Table of Contents to State Backends page
  - Hierarchical restart strategies sections
- CEP => Event Processing (CEP)

This closes #1705.

This closes #1581

This closes #1688.

This closes #1588

This closes #1663

This adds dedicated WindowAssigners for processing time and event time.
timeWindow() and timeWindowAll() respect the TimeCharacteristic set
on the StreamExecutionEnvironment.

This will make the easy stuff easy, i.e. using time windows and quickly
switching the time characteristic. Users will then have the flexibility
to mix different kinds of window assigners in their job.

This also expands the translation tests to verify that the correct
window operators are instantiated.

[FLINK-3420] [api-breaking] Remove utility functions 'readTextFileWithValue' and 'readFileOfPrimitives' from StreamExecutionEnvironment

These methods are highly specific for very niche cases of bounded data stream processing.
As such, the disadvantages (bloat and lock the API, lock the development into support) outweigh the benefit.

This closes #1648

This closes #1563

This closes #1524

Update index.js and reset vendor.css and vendor.js to master version

Update web-dashboard

Remove duplicate flink-runtime-web dependency from flink-tests

Remove not used ProgramStopException

Change stopping behaviour to only work in job status RUNNING

This closes #750.

- added JobType to JobGraph and ExecutionGraph
- added interface Stoppable, applied to SourceStreamTask
- added STOP signal logic to JobManager, TaskManager, ExecutionGraph
- extended Client to support stop
- extended Cli frontend, JobManager frontend
- updated documenation

Fix JobManagerTest.testStopSignal and testStopSignalFail

The StoppableInvokable could not be instantiated by Task because it was declared as a private
class. Adds additional checks to verify that the stop signal behaves correctly.

Auto-detect if job is stoppable

A job is stoppable iff all sources are stoppable

- Replace JobType by stoppable flag
- Add StoppableFunction and StoppableInvokable to support the optional stop operation
- added REST get/delete test (no extra YARN test -- think not required as get/delete is both tested)
- bug fix: job got canceld instead of stopped in web interface
- Add StoppingException
- Allow to stop jobs when they are not in state RUNNING

Second round of Till's comments

A RestartStrategy defines how the ExecutionGraph reacts in case of a restart. Different strategies
are conceivable. For example, no restart, fixed delay restart, exponential backoff restart, scaling
in/out restart, etc.

Expose RestartStrategy to user API

This removes the setNumberExecutionRetries and the setDelayBetweenRetries on the ExecutionEnvironment and
the ExecutionConfig. Instead the more general RestartStrategy can be set. In order to maintain the
separation between the runtime and api module, one sets a RestartStrategyConfiguration which is transformed
into a RestartStrategy on the JobManager.

Replace old execution-retries configuration parameters by restart-strategy.

Add FixedDelayRestartStrategy test case

Reintroduce old configuration values and API calls for the deprecated restart mechanism

The old configuration values and API calls will be respected if no explicit
RestartStrategy has been set. The values, if correct, are used to instantiate
a FixedDelayRestartStrategy.

Add deprecation comments to the JavaDocs

Add logging statement for job recovery

Fix JobManagerProcessFailureBatchRecoveryITCase by introducing a job recovery timeout

Add proper annotations to RestartStrategies

Let ExecutionGraphRestartTest extend TestLogger

This closes #1470.

Adds a new per-job tab displaying subtask statistics aggregated by TaskManager.

This closes #1564.

This closes #1618

This is the Javadoc of DataStream.rescale() that describes the
behaviour:

Sets the partitioning of the {@link DataStream} so that the output elements
are distributed evenly to a subset of instances of the next operation in a round-robin
fashion.

The subset of downstream operations to which the upstream operation sends
elements depends on the degree of parallelism of both the upstream and downstream operation.
For example, if the upstream operation has parallelism 2 and the downstream operation
has parallelism 4, then one upstream operation would distribute elements to two
downstream operations while the other upstream operation would distribute to the other
two downstream operations. If, on the other hand, the downstream operation has parallelism
2 while the upstream operation has parallelism 4 then two upstream operations will
distribute to one downstream operation while the other two upstream operations will
distribute to the other downstream operations.

In cases where the different parallelisms are not multiples of each other one or several
downstream operations will have a differing number of inputs from upstream operations.

This closes #1592.

Old guides are redirected to the new pages.

Implements NFA using the SharedBuffer

Implements NFACompiler to compile a Pattern into a NFA

Add CEP operator

Makes NFA and SharedBuffer serializable

Add serializability support to SharedBuffer and NFA

Add keyed cep pattern operator

Adds CEP documentation

Adds online documentation for the CEP library

Copies sequence events before giving them to the UDF

Fix correct scala type suffixes

This closes #1557.

This closes #1514

Henceforth, we shall only use the term lower in the context of timestamps
to denote that an event has occurred before another event.