We are still shaking out bugs and features, so make sure you test this in your setup before deploying it to production.

We have tested with, and recommend the use of, Hadoop 0.20.203 or Cloudera CHD3 (Which ships 0.20.2)

The latest builds are tested primarily against MongoDB 1.8+ but should still work with 1.6.x

NOTE: We have not tested this driver with Hadoop 0.21 yet. Hadoop lists 0.21 as "unstable, unsupported " and until that changes we will not provide any full support.

• Brendan McAdams [email protected]
• Eliot Horowitz [email protected]

• Sarthak Dudhara [email protected] (BSONWritable comparable interface)
• Priya Manda [email protected] (Test Harness Code)
• Rushin Shah [email protected] (Test Harness Code)
• Joseph Shraibman [email protected] (Sharded Input Splits)
• Sumin Xia [email protected] (Sharded Input Splits)

This is currently under development and is not feature complete.

However, the core functionality is relatively stable

It should be considered an early beta.

You will need the MongoDB Java Driver 2.5.3+ or master.

Issue tracking: https://github.com/mongodb/mongo-hadoop/issues

Discussion: http://groups.google.com/group/mongodb-user/

The following features are presently supported:

Working Input and Output adapters for MongoDB are provided. These can be configured by XML or programatically - see the WordCount examples for demonstrations of both approaches. You can specify a query, fields and sort specs in the XML config as JSON or programatically as a DBObject.

Sharding is currently NOT supported explicitly (e.g. we don't use the chunks to read from individual shards).

There are presently NO input splits - your entire collection is passed as a single split to a single mapper. If you have a problem which requires more discreet splits please email us to describe your problem

The MongoStorage Pig module is provided; it currently only supports saving to MongoDB. Load support will be provided at a later date.

There are two example WordCount processes for Hadoop MapReduce in examples/wordcount Both read strings from MongoDB and save the count of word frequency.

They are configured to read documents in db test, collection in, where the string to count frequency of is defined in field x.

The results will be saved in db test, collection out.

WordCount.java is a programatically configured MapReduce job, where all of the configuration params are setup in the Java code. You can run this with the ant task wordcount.

WordCountXMLConfig.java is configured purely through XML files, with JSON for queries, etc. See examples/wordcount/resources/mongo-wordcount.xml for the example configuration. You can run this with the ant task wordcountXML, or with a hadoop command of:

hadoop jar mongo-hadoop.jar com.mongodb.hadoop.examples.WordCountXMLConfig -conf examples/wordcount/resources/mongo-wordcount.xml

You will need to copy the mongo-java-driver.jar file into your Hadoop lib directory before this will work.

The treasury yield example demonstrates working with a more complex input BSON document and calculating an average.

It uses a database of daily US Treasury Bid Curves from 1990 to Sept. 2010 and runs them through to calculate annual averages.

There is a JSON file examples/treasury_yield/resources/yield_historical_in.json which you should import into the yield_historical.in collection in the demo db.

The sample data can be imported into the mongos host by calling (assumes mongos running on 27017 on the same node):

mongoimport --db demo --collection yield_historical.in --type json --file examples/treasury_yield/resources/yield_historical_in.json

Once the data is imported, the test can be run by executing (on the Hadoop master):

hadoop jar mongo-hadoop.jar com.mongodb.hadoop.examples.TreasuryYieldXMLConfig -conf examples/treasury_yield/resources/mongo-treasury_yield.xml

To confirm the test ran successfully, look at the demo database and query the yield_historical.out collection.

###Pig

We presently provide a modified version of the Pig Tutorial from the Pig distribution for testing.

This script differs from the pig tutorial in that it saves the job results to MongoDB.

The use of Pig assumes you have Hadoop & Pig installed and setup on your machine...

Make sure you've built using ant jar and then run:

pig -x local examples/test.pig

You should find the results in the 'test' DB inside the 'pig.output' collection.

• Pick reasonable split points for non-sharded collections
  • For initial release, no splits for non-sharded collections
• Elastic map/reduce support?
• Support for "Merge" Jobs (e.g. combine results of multiple map/reduces esp. from diff. inputs in a single join job - this is supported by Hadoop w/ implementation of special interfaces)
• Support Streaming for Python/Ruby implementation
• Full support for appropriate 'alternate' Hadoop Interfaces
  • We already support Pig for Output (get input working)
  • Cascading Seems to be popular as well and should be evaluated

You cannot configure bare regexes (e.g. /^foo/) in the config xml as they won't parse. Use {"$regex": "^foo", "$options": ""} instead. .. Make sure to omit the slashes.

Running Streaming: hadoop jar $HADOOP_STREAMING -conf examples/treasury_yield/resources/mongo-treasury_yield.xml -libjars mongo-hadoop.jar,lib/mongo-java-driver-2.4.jar -mapper examples/treasury_yield/src/mapper.py -reducer examples/treasury_yield/src/reducer.py -inputformat com.mongodb.hadoop.mapred.MongoInputFormat -outputformat com.mongodb.hadoop.mapred.MongoOutputFormat -input README.md -output foo.md

You will need Hadoop Streaming 0.21 or higher to make this work --- 0.20.2 does not support Binary streaming

hadoop jar $HADOOP_STREAMING -D stream.map.input=rawbytes -conf examples/treasury_yield/resources/mongo-treasury_yield.xml -libjars mongo-hadoop.jar,lib/mongo-java-driver-2.4.jar -mapper examples/treasury_yield/src/mapper.py -reducer examples/treasury_yield/src/reducer.py -inputformat com.mongodb.hadoop.mapred.MongoInputFormat -outputformat com.mongodb.hadoop.mapred.MongoOutputFormat -input README.md -output foo.md

hadoop jar $HADOOP_STREAMING -conf examples/treasury_yield/resources/mongo-treasury_yield.xml -libjars mongo-hadoop.jar,lib/mongo-java-driver-2.4.jar -mapper examples/treasury_yield/src/mapper.py -reducer examples/treasury_yield/src/reducer.py -inputformat com.mongodb.hadoop.mapred.MongoInputFormat -outputformat com.mongodb.hadoop.mapred.MongoOutputFormat -input README.md -output foo.md -io rawbytes

hadoop jar $HADOOP_STREAMING -libjars mongo-hadoop.jar,lib/mongo-java-driver-2.4.jar -mapper examples/treasury_yield/src/mapper.py -reducer examples/treasury_yield/src/reducer.py -inputformat com.mongodb.hadoop.mapred.MongoInputFormat -outputformat com.mongodb.hadoop.mapred.MongoOutputFormat -input mongodb://localhost/demo.yield_historical.in -output mongodb://localhost/demo.yield_historical.out

hadoop jar ./mongo-hadoop-streaming.jar -libjars mongo-hadoop.jar,lib/mongo-java-driver-2.4.jar -mapper examples/treasury_yield/src/mapper.py -reducer examples/treasury_yield/src/reducer.py -inputformat com.mongodb.hadoop.mapred.MongoInputFormat -outputformat com.mongodb.hadoop.mapred.MongoOutputFormat -input mongodb://localhost/demo.yield_historical.in -output mongodb://localhost/demo.yield_historical.out

hadoop jar mongo-hadoop-streaming.jar -libjars $HADOOP_STREAMING,mongo-hadoop.jar,lib/mongo-java-driver-2.4.jar -mapper examples/treasury_yield/src/mapper.py -reducer examples/treasury_yield/src/reducer.py -inputformat com.mongodb.hadoop.mapred.MongoInputFormat -outputformat com.mongodb.hadoop.mapred.MongoOutputFormat -input mongodb://localhost/demo.yield_historical.in -output mongodb://localhost/demo.yield_historical.out