hRaven collects run time data and statistics from map reduce jobs running on Hadoop clusters and stores the collected job history in an easily queryable format. For the jobs that are run through frameworks (Pig or Scalding/Cascading) that decompose a script or application into a DAG of map reduce jobs for actual execution, hRaven groups job history data together by an application construct. This allows for easier visualization of all of the component jobs' execution for an application and more comprehensive trending and analysis over time.
- Apache HBase (1.1.3) - a running HBase cluster is required for the hRaven data storage
- Apache Hadoop - hRaven current supports collection of job data on specific
versions of Hadoop:
- Hadoop 2.6+ post hRaven 1.0.0 Hadoop 1 will no longer be supported
- JRE 8 - As of hRaven 1.0.0 Java 8 jars are generated. Use hRaven 0.9.x for Java 7 runtimes.
Clone the github repo or download the latest release:
git clone git://github.com/twitter/hraven.git
If you cloned the repository, build the full tarball:
mvn clean package assembly:single
Extract the assembly tarball on a machine with HBase client access.
Create the initial schema
hbase [--config /path/to/hbase/conf] shell bin/create_schema.rb
hRaven requires the following HBase tables in order to store data for map reduce jobs:
job_history- job-level statistics, one row per jobjob_history_task- task-level statistics, one row per task attemptjob_history-by_jobId- index table pointing tojob_historyrow by job IDjob_history_app_version- distinct versions associated with an application, one row per applicationjob_history_raw- stores the raw job configuration and job history files, as byte[] blobsjob_history_process- meta table storing progress information for the data loading processflow_queue- time based index of flows for Ambrose integrationflow_event- stores flow progress events for Ambrose integration
The initial table schema can be created by running the create_schema.rb
script:
hbase [--config /path/to/hbase/conf] shell bin/create_schema.rb
Currently, hRaven loads data for completed map reduce jobs by reading and parsing the job history and job configuration files from HDFS. As a pre-requisite, the Hadoop Job Tracker must be configured to archive job history files in HDFS, by adding the following setting to your mapred-site.xml file:
<property>
<name>mapred.job.tracker.history.completed.location</name>
<value>hdfs://<namenode>:8020/hadoop/mapred/history/done</value>
<description>Store history and conf files for completed jobs in HDFS.
</description>
</property>
Once your Job Tracker is running with this setting in place, you can load data into hRaven with a series of map reduce jobs:
- JobFilePreprocessor - scans the HDFS job history archive location for newly completed jobs; writes the new filenames to a sequence file for processing in the next stage; records the sequence file name in a new row in the
job_history_processtable - JobFileRawLoader - scans the processing table for new records from JobFileProcessor; reads the associated sequence files; writes the associated job history files for each sequence file entry into the HBase
job_history_rawtable - JobFileProcessor - reads new records from the raw table; parses the stored job history contents into individual puts for the
job_history,job_history_task, and related index tables
Each job has an associated shell script under the bin/ directory. See these scripts for more details on the job parameters.
Once data has been loaded into hRaven tables, a REST API provides access to job data for common query patterns. hRaven ships with a simple REST server, which can be started or stopped with the command:
./bin/hraven-daemon.sh (start|stop) rest
The following endpoints are currently supported:
Path: /job/<cluster>[/jobId]
Returns: single job
Optional QS Params: n/a
Path: /jobFlow/<cluster>[/jobId]
Returns: the flow for the jobId
Optional QS Params - v1:
limit(default=1)
Path: /flow/<cluster>/<user>/<appId>[/version]
Returns: list of flows
Optional QS Params - v1:
limit(default=1) - max number of flows to returnincludeConf- filter configuration property keys to return only the given namesincludeConfRegex- filter configuration property keys to return only those matching the given regex patterns
Path: /flowStats/<cluster>/<user>/<app>
Returns: list of flows with only minimal stats
Optional QS params:
version(optional filter)startRow(base64 encoded row key)startTime(ms since epoch) - restrict results to given time windowendTime(ms since epoch) - restrict results to given time windowlimit(default=100) - max flows to returnincludeJobs(boolean flag) - include per-job details
Note: This endpoint duplicates functionality from the "/flow/" endpoint and maybe be combined back in to it in the future.
Path: /tasks/<cluster>/[jobId]
Returns: task details of that single job
Path: /appVersion/<cluster>/<user>/<app>
Returns: list of distinct app versions
Optional QS params:
limit- max results to return
Path: /newJobs/<cluster>/
Returns: list of apps with only minimal stats
Optional params:
startTime(epoch timestamp in milliseconds)endTime(epoch timestamp in milliseconds)limit(max rows to return)user(user name to filter it by)
Have a bug? Please create an issue here on GitHub https://github.com/twitter/hraven/issues
Have a question? Ask on our mailing list!
hRaven Users:
hRaven Developers:
For more details on how to contribute to hRaven, see CONTRIBUTING.md.
- While hRaven stores the full data available from job history logs, the rolled-up statistics in the
Flowclass only represent data from sucessful task attempts. We plan to extend this so that theFlowclass also reflects resources used by failed and killed task attempts.
Copyright 2016 Twitter, Inc. and other contributors
Licensed under the Apache License Version 2.0: http://www.apache.org/licenses/LICENSE-2.0