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[SPARK-4026][Streaming] Write ahead log management

Hari Shreedharan authored 10 years ago

As part of the effort to avoid data loss on Spark Streaming driver failure, we want to implement a write ahead log that can write received data to HDFS. This allows the received data to be persist across driver failures. So when the streaming driver is restarted, it can find and reprocess all the data that were received but not processed.

This was primarily implemented by @harishreedharan. This is still WIP, as he is going to improve the unitests by using HDFS mini cluster.

Author: Hari Shreedharan <hshreedharan@apache.org>
Author: Tathagata Das <tathagata.das1565@gmail.com>

Closes #2882 from tdas/driver-ha-wal and squashes the following commits:

e4bee20 [Tathagata Das] Removed synchronized, Path.getFileSystem is threadsafe
55514e2 [Tathagata Das] Minor changes based on PR comments.
d29fddd [Tathagata Das] Merge pull request #20 from harishreedharan/driver-ha-wal
a317a4d [Hari Shreedharan] Directory deletion should not fail tests
9514dc8 [Tathagata Das] Added unit tests to test reading of corrupted data and other minor edits
3881706 [Tathagata Das] Merge pull request #19 from harishreedharan/driver-ha-wal
4705fff [Hari Shreedharan] Sort listed files by name. Use local files for WAL tests.
eb356ca [Tathagata Das] Merge pull request #18 from harishreedharan/driver-ha-wal
82ce56e [Hari Shreedharan] Fix file ordering issue in WALManager tests
5ff90ee [Hari Shreedharan] Fix tests to not ignore ordering and also assert all data is present
ef8db09 [Tathagata Das] Merge pull request #17 from harishreedharan/driver-ha-wal
7e40e56 [Hari Shreedharan] Restore old build directory after tests
587b876 [Hari Shreedharan] Fix broken test. Call getFileSystem only from synchronized method.
b4be0c1 [Hari Shreedharan] Remove unused method
edcbee1 [Hari Shreedharan] Tests reading and writing data using writers now use Minicluster.
5c70d1f [Hari Shreedharan] Remove underlying stream from the WALWriter.
4ab602a [Tathagata Das] Refactored write ahead stuff from streaming.storage to streaming.util
b06be2b [Tathagata Das] Adding missing license.
5182ffb [Hari Shreedharan] Added documentation
172358d [Tathagata Das] Pulled WriteAheadLog-related stuff from tdas/spark/tree/driver-ha-working

6a40a768

6a40a768 10 years ago

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Apache Spark

Spark is a fast and general cluster computing system for Big Data. It provides high-level APIs in Scala, Java, and Python, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for stream processing.

http://spark.apache.org/

Online Documentation

You can find the latest Spark documentation, including a programming guide, on the project web page. This README file only contains basic setup instructions.

Building Spark

Spark is built using Apache Maven. To build Spark and its example programs, run:

mvn -DskipTests clean package

(You do not need to do this if you downloaded a pre-built package.) More detailed documentation is available from the project site, at "Building Spark with Maven".

Interactive Scala Shell

The easiest way to start using Spark is through the Scala shell:

./bin/spark-shell

Try the following command, which should return 1000:

scala> sc.parallelize(1 to 1000).count()

Interactive Python Shell

Alternatively, if you prefer Python, you can use the Python shell:

./bin/pyspark

And run the following command, which should also return 1000:

>>> sc.parallelize(range(1000)).count()

Example Programs

Spark also comes with several sample programs in the examples directory. To run one of them, use ./bin/run-example <class> [params]. For example:

./bin/run-example SparkPi

will run the Pi example locally.

You can set the MASTER environment variable when running examples to submit examples to a cluster. This can be a mesos:// or spark:// URL, "yarn-cluster" or "yarn-client" to run on YARN, and "local" to run locally with one thread, or "local[N]" to run locally with N threads. You can also use an abbreviated class name if the class is in the examples package. For instance:

MASTER=spark://host:7077 ./bin/run-example SparkPi

Many of the example programs print usage help if no params are given.

Running Tests

Testing first requires building Spark. Once Spark is built, tests can be run using:

./dev/run-tests

Please see the guidance on how to run all automated tests.

A Note About Hadoop Versions

Spark uses the Hadoop core library to talk to HDFS and other Hadoop-supported storage systems. Because the protocols have changed in different versions of Hadoop, you must build Spark against the same version that your cluster runs.

Please refer to the build documentation at "Specifying the Hadoop Version" for detailed guidance on building for a particular distribution of Hadoop, including building for particular Hive and Hive Thriftserver distributions. See also "Third Party Hadoop Distributions" for guidance on building a Spark application that works with a particular distribution.

Configuration

Please refer to the Configuration guide in the online documentation for an overview on how to configure Spark.