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Apache Oozie is a workflow scheduler system to manage Apache Hadoop jobs.

Oozie is a job scheduler with fancy features. Most relevantly, jobs may be scheduled based on the existence of data in HDFS. This allows jobs to be scheduled to be run not based only on a current timestamp, but for when the data needed to run a particular job is available.

Some terms

An action generally represents a single step in a job workflow. Examples include pig scripts, failure notifications, map-reduce jobs, etc.
Workflows are used to chain actions together. A workflow is synonymous with a job. Workflows describe how actions should run, and how actions should flow. Actions can be chained based on success and failure conditions.
Coordinators are used to schedule recurring runs of workflows. They can abstractly describe input and output datasets based on on periodicity. Coordinators will submit workflow jobs based on the existence of data.

A bundle is a logical grouping of coordinators that share commonalities. You can use bundles to start and stop whole groups of coordinators at once.

Oozie 101. An Example

Let's run through a simple example of how to set up runs of an Oozie job running on the cluster. Have in mind that this is an example just to get you started and that more steps than the ones outlined below are needed to get a job running according to our production standards.

In our example we will run via Oozie a job that runs a parametized hive query. Note that we assume you have access to stat1004.eqiad.wmnet from which we normally access the Analytics Cluster.

Something to know is that Oozie overrides hive default and forces it to use only 1 reducer for its map-reduce jobs. If you want to let hive decide on the number of reducers it should use (default behavior), then explicitly set mapred.reduce.tasks to -1 (see below in the workflow.xml file)


The job we are going to set up will use just a workflow, this means that -in the absence of a coordinator - we will run it by hand using the Oozie command line interface (CLI). There is a lot you can do through Oozie's CLI, please take a look at docs [here]

There are three files needed:

  • A file with the hive query.
  • A workflow.xml file that oozie is going to use to see what job to run
  • A file that sets concrete values for the properties defined in the workflow.

Both workflow.xml and the hive query need to be available inside HDFS, so we will be putting them into HDFS /tmp directory and the Oozie job will run from there.

hive query

Please note placeholders for parameters and replace <user> with your username.

 DROP VIEW IF EXISTS <user>_oozie_test;
 CREATE VIEW <user>_oozie_test AS
 CASE WHEN user_agent LIKE('%iPhone%') THEN 'iOS'
  ELSE 'Android' END AS platform,
 parse_url(concat('', uri_query), 'QUERY', 'appInstallID') AS uuid
    FROM ${source_table}
    WHERE year=${year}
        AND month=${month}
        AND day=${day}
        AND hour=${hour};

-- Now get a count of totals that will be inserted in some file
INSERT OVERWRITE DIRECTORY "${destination_directory}"
SELECT platform, COUNT(DISTINCT(uuid))
FROM <user>_oozie_test
GROUP BY platform;

Workflow.xml and

<workflow-app name="cmd-param-demo" xmlns="uri:oozie:workflow:0.4">

        <!-- Required properties -->

            <description>hive-site.xml file path in HDFS</description>
        <!-- specifying parameter values in file to test running -->
                Hive table to read data from.
            <description>The partition's year</description>
            <description>The partition's month</description>
            <description>The partition's day</description>
            <description>The partition's hour</description>

    <start to="hive-demo"/>
    <action name="hive-demo">
        <hive xmlns="uri:oozie:hive-action:0.2">
                <!--Let hive decide on the number of reducers -->

        <ok to="end"/>
        <error to="kill"/>
    <kill name="kill">
        <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
    <end name="end"/>

@stat1004:~/workplace/refinery/oozie/mobile-apps/generate_daily_uniques$ more
name_node                         = hdfs://analytics-hadoop
job_tracker                       =
queue_name                        = default
oozie_directory                   = ${name_node}/wmf/refinery/current/oozie
# for testing locally, this won't work:
# hive_site_xml                   = ${oozie_directory}/util/hive/hive-site.xml
hive_site_xml                     = ${refinery_directory}/oozie/util/hive/hive-site.xml
# Workflow app to run.         = hdfs://analytics-hadoop/tmp/tests-<some>/workflow.xml
oozie.use.system.libpath          = true
oozie.action.external.stats.write = true
# parameters
source_table = wmf_raw.webrequest
year = 2014
month = 11
day = 20
hour = 10
user = <your-user-in1002>

Validating worflow.xml

After creating the files you should make sure they are valid according to oozie's schema:

oozie validate workflow.xml

Moving files to hdfs

The easiest place where to put stuff is the /tmp directory. You should move there the workflow.xml and hive file

hdfs dfs -mkdir  /tmp/tests-$USER
hdfs dfs -put workflow.xml  /tmp/tests-$USER/workflow.xml
hdfs dfs -cat /tmp/tests-$USER/workflow.xml

Running oozie job

From your local directory -where you have run:

oozie job -config -run

Running your job, say, once a day

In order to use oozie's crontab you will need a coordinator file

Good docs about coordinators can be found here: [1]

Running a real oozie example

The main difference with the 101 example is that in this case we will likely need to override the oozie directory. This testing needs to be done from 1002/1004. Let's assume that your refinery code you want to test is deployed to ~/workplace/refinery/oozie

Rsync code to 1002/1004

rsync -rva --delete ./oozie/ stat1002.eqiad.wmnet:~/oozie

Create tables if needed

If your oozie job accesses new tables you would need to create them in your db, rememeber you are working of your user space

hive -f blah.hql --database nuria

Put your oozie directory on hdfs

>nuria@stat1004:~/some$ ls oozie
>hdfs dfs -rmr /tmp/oozie-nuria ; hdfs dfs -mkdir /tmp/oozie-nuria; hdfs dfs -put oozie/ /tmp/oozie-nuria

Run oozie job overriding what pertains

Note that we are overriding the refinery-directory variable

oozie job -run -Duser=nuria -Darchive_directory=hdfs://analytics-hadoop/tmp/nuria -Doozie_directory=/tmp/oozie-nuria/oozie -config ./oozie/pageview/hourly/  -Dstart_time=2015-09-03T00:00Z -Dstop_time=2015-09-03T04:00Z -Drefinery_directory=hdfs://analytics-hadoop$(hdfs dfs -ls -d /wmf/refinery/2015* | tail -n 1 | awk '{print $NF}')


Checking logs:

oozie job -log <job_id>

Seeing the last couple jobs that run:

oozie jobs -localtime -len 2

Get more info on a job id that failed

oozie job -info <job-id>

This should display your hadoop job id (see below)

Job ID : 0005783-141210154539499-oozie-oozi-W
Workflow Name : cmd-param-demo
App Path      : hdfs://analytics-hadoop/tmp/tests-mobile-apps/workflow.xml
Status        : KILLED
Run           : 0
CoordAction ID: -

ID                                                                            Status    Ext ID                 Ext Status Err Code
0005783-141210154539499-oozie-oozi-W@:start:                                  OK        -                      OK         -
0005783-141210154539499-oozie-oozi-W@hive-demo                                ERROR     job_1415917009743_45854 FAILED/KILLED40000 
0005783-141210154539499-oozie-oozi-W@kill                                     OK        -                      OK         E0729

Logs for hadoop job id: 1415917009743_45854

Should be at:

>yarn logs --applicationId  application_1415917009743_45854

Also, you can try:

Kill a job

Get job id from following command:

>oozie jobs  -jobtype coord
>oozie job  -kill <id>

Check how the cluster is doing

You can see how the queues are being utilized here:


You'll have to set up the ssh tunnel as specified in Analytics/Cluster/Access

More info

Naming Convention

Refinery oozie jobs follow a naming convention allowing to automate job restart (see below). This convention is based on folders in which jobs configuration files are stored. The base folder for the convention is, in refinery git repo, the oozie folder.

  • Each refinery top level job (no parent job) is named after its folder hierarchy with - instead of /, with either -bundle or -coord as a postfix. For instance, the webrequest/load/ defined job is named webrequest-load-bundle.
  • Children jobs follow the same pattern, except they are postfixed with parameters information. For instance, coordinator jobs lauched by webrequest-load-bundle are webrequest-load-coord-upload, webrequest-load-coord-text, webrequest-load-coord-maps and webrequest-load-coord-misc.

How to see jobs scheduled to run

The bird's eye view over currently submitted Refinery Oozie jobs is depicted in the following diagram:


On stat1004 run

 oozie jobs -jobtype bundle -filter status=RUNNING

to see the 100 most recent, RUNNING bundles.

On stat1004 run

 oozie jobs -jobtype coordinator -filter status=RUNNING

to see the 100 most recent, RUNNING coordinators

On stat1004 run

 oozie jobs -jobtype wf -filter status=RUNNING

to see the 100 most recent, RUNNING workflows.

To consider more than the 100 jobs, add a -len option at the end. Like -len 2000 to get the 2000 most recent ones.

To not limit to RUNNING jobs, drop the -filter status=RUNNING from the command.

The source for the refinery's oozie production jobs can be found at .

In the cluster, Oozie's job definitions can be found at /wmf/refinery/....

Never deploy jobs from the /wmf/refinery/current/..., always use one of refinery-variants that have a concrete time and commit in the directory name. Like /wmf/refinery/2015-01-09T12.39.20Z--2007cb8.


Documentation intended for analytics team on how to restart jobs in the cluster and such: Analytics/Cluster/Oozie/Administration