How To Test Pig

This document covers how to test Pig. It is intended for Pig developers who need to know how to test their work. It can also be used by Pig users who wish to verify their instance of Pig.

Pig currently provides tools for two types of testing: unit testing and end-to-end testing.

Unit Testing

Unit tests are executed via JUnit. Currently, many "unit tests" are really end-to-end tests. We are in the process of changing this so that all of end-to-end tests will be run by the e2e harness (see below). See PigTestProposal for details.


Prior to running unit tests, make sure to set umask 0022.

We also see unit tests fail due to extended acl, so use setfacl -b to remove extended acl if applicable.

Running all unit tests

To run the unit tests do ant test in the top level Pig directory. Currently this takes 8 hours to run. We intend to drive this to under five minutes. Until this is done it is not expected that contributors will run all these tests before submitting their patch.

Running pre-commit tests

You can also run ant clean test-commit to run true unit tests plus a few very basic end-to-end tests to assure nothing fundamental has been broken. We ask that committers run this before committing patches, and that contributors run it before uploading their patch.

Running a single unit test

A single unit test can be run by setting the testcase property. For example:

ant -Dtestcase=TestRegisteredJarVisibility clean test

Generating Code Coverage Numbers for Unit Tests

Pig is integrated with clover, which can be used to measure code coverage of the unit tests. First, you will need to obtain clover:

  1. Download clover from Atlassian. You want Clover for Ant 2.6.3. The license from Apache doesn't work with the latest 3.x versions of Clover.
  2. Unzip clover somewhere on the machine where you will be doing the tests. We'll call this location $CLOVER_HOME
  3. Download the license file from Apache. You must be an Apache committer to access this file.
  4. Place the license file in $CLOVER_HOME/lib

Now, to run the unit tests with clover:

ant clean
ant -Dclover.home=<clover_home> -Drun.clover=true clover jar test
ant -Dclover.home=<clover_home> -Drun.clover=true generate-clover-reports
ant -Dclover.home=<clover_home> -Drun.clover=true generate-pdf-clover-reports

The detailed report is now available as a collection of HTML files under build/test/clover/reports
A summary report is now available in build/test/clover/pdf/reports/clover_coverage.pdf

End-to-end Testing

End-to-end tests (e2e) are run with a custom test harness. For information on this harness see TestHarnessDesign. The goal of these tests is to test Pig on a real Hadoop cluster. These tests try to cover all functionality provided by Pig.

Currently running the entire suite of e2e tests takes about 10 hours. It is not expected that contributors committers will run all these tests before contributing or committing a patch. They should run the Checkin tests, plus any tests they have added, plus tests that cover the area of changes they are making. For example, if one was making a change to the merge join algorithm, he should run the Checkin tests plus the MergeJoin tests before uploading and checking in his patch. These tests should be run in both cluster and local mode.

How to Run e2e Tests

Running the e2e tests requires three things: a cluster to run them on, an old version of Pig to use to generate expected results, and perl (plus a few CPAN modules) on your client machine. The cluster can be quite small. A single machine will enough. Since performance is not the goal it is fine if this is a virtual machine. If you do not have access to a cluster, see below for information on how to run the tests on EC2.

You will need the following CPAN modules:

  • IPC::Run
  • Parallel::ForkManager
  • DBI

For help installing CPAN modules, see cpan module install instructions .

Currently we are using Pig 0.8.1 for the old version of Pig that generates expected results. Once 0.9 is widely adopted we will likely switch to it as the source of truth. You can download Pig 0.8.1 from

If you are running in a secure Hadoop environment (with kerberos in use), you must do kinit to obtain a ticket before running ant. Otherwise your tests will all fail to gain access to the cluster.

Before you can run the test harness against your cluster for the first time, you must generate the test data in your cluster. To do this, do:

ant -Dharness.old.pig=old_pig -Dharness.cluster.conf=hadoop_conf_dir -Dharness.cluster.bin=hadoop_script -Dharness.hadoop.home=hadoop_home_dir test-e2e-deploy

Where old_pig is where you installed the old version of Pig, hadoop_conf_dir is the directory where your hadoop-site.xml or mapred-site.xml file is, and hadoop_script is where your hadoop executable is located. For example, if you have installed Pig 0.8.1 in /usr/local/pig/pig-0.8.1 and Hadoop in /usr/local/hadoop, then your command line would look like:

ant -Dharness.old.pig=/usr/local/pig/pig-0.8.1 -Dharness.cluster.conf=/usr/local/hadoop/conf -Dharness.cluster.bin=/usr/local/hadoop/bin/hadoop -Dharness.hadoop.home=hadoop_home_dir test-e2e-deploy

This takes a couple of minutes and only needs to be run once. After building Pig itself it will display information on the data it is generating.

Once you have loaded your cluster with data, you can run the tests by doing:

ant -Dharness.old.pig=old_pig -Dharness.cluster.conf=hadoop_conf_dir -Dharness.cluster.bin=hadoop_script -Dharness.hadoop.home=hadoop_home_dir test-e2e

Run with test-e2e-tez instead of test-e2e to run tests with Tez as execution engine.

Running the full test suite is rarely what you want, as it takes around 10 hours. If you are running against a cluster with more capacity, you can speedup the execution of the tests by parallelizing it. The fork.factor.conf.file property tells how many test conf files to run in parallel. The property tells how many groups to run in parallel within each test file. Within a group, each tests are run sequentially.  For eg:  -Dfork.factor.conf.file=2 will run 2 test files and 5 groups in each totaling 10 tests in parallel.

To run only some tests, set the property. This value can be passed a group of tests (e.g. Checkin), or a single test (e.g. Checkin_1). You can pass multiple tests or groups in this property. Each test or group of tests must be proceeded by a {{-t }}. For example, to run the Checkin tests and the first MergeJoin test, do:

ant -Dharness.old.pig=old_pig -Dharness.cluster.conf=hadoop_conf_dir -Dharness.cluster.bin=hadoop_script -Dharness.hadoop.home=hadoop_home_dir"-t Checkin -t MergeJoin_1" test-e2e

Status will be provided as each test is run. Tests either succeed, fail, or abort. A test fails when actual results do not match expected results. A test aborts when the test or expected results generation failed to execute. The harness prints out the path to the log file where details of the test run are provided.

If you want to clean the data off of your cluster, you can use the undeploy target:

ant -Dharness.old.pig=old_pig -Dharness.cluster.conf=hadoop_conf_dir -Dharness.cluster.bin=hadoop_script -Dharness.hadoop.home=hadoop_home_dir test-e2e-undeploy

There is no need to do this on a regular basis.

If you want to generate a junit format xml file out of the e2e test log and use it for displaying test results in Jenkins, you can run test/e2e/harness/ against the log file.

 test/e2e/harness/ testdist/out/log/test_harnesss_1411157020 > test-report.xml

Running e2e in Local Mode

End-to-end tests can also be run in local mode. While this is not a substitute for running them on a cluster, it is a good idea to run your tests in both cluster and local mode to assure both modes work. Running in local mode is nearly identical to running cluster mode, except that the test data in local mode is placed in a directory under the test harness. So you must generate the local mode data each time you are working in a different source tree or after doing an ant clean.

To generate the test data in local mode, do:

ant -Dharness.old.pig=old_pig -Dharness.cluster.conf=hadoop_conf_dir -Dharness.cluster.bin=hadoop_script -Dharness.hadoop.home=hadoop_home_dir test-e2e-deploy-local

(Yes you still have to give cluster information even though you aren't using a cluster. Pig doesn't use it in this case and you can pass bogus info if you want.)

To run the local mode tests themselves, do:

ant -Dharness.old.pig=old_pig -Dharness.cluster.conf=hadoop_conf_dir -Dharness.cluster.bin=hadoop_script -Dharness.hadoop.home=hadoop_home_dir test-e2e-local

Running on EC2

If you do not have access to a cluster you can run the tests in EC2. In the directory tests/e2e/pig/whirr there are tools that will help you run on EC2.

In the following text any value that starts your_ is a value you should fill in.


  1. An account in Amazon's AWS
  2. An Amazon Access Key ID and Secret Access Key. These are not ssh keys. See under Access Credentials. You need an Access Key.
  3. An RSA SSH key pair that is passphraseless. You may want to generate a pair just for use with the tool to avoid forcing your regular ssh key pair to be passphraseless. They must be RSA; Whirr does not work with any of the other key types. You can generate a pair with the command ssh-keygen -f your_private_rsa_key_file -t rsa -P '' where your_private_rsa_key_file is the file to store the private key in.
  4. Apache Whirr version 0.5 or newer.

To Start a Cluster:

export AWS_ACCESS_KEY_ID=your_amazon_access_key
export AWS_SECRET_ACCESS_KEY=your_secret_amazon_access_key
export SSH_PRIVATE_KEY_FILE=your_private_rsa_key_file
cd your_path_to_apache_whirr/bin
./whirr launch-cluster --config your_path_to_pig_trunk/test/e2e/pig/whirr/

This will take ~5 minutes and spew various messages on your screen.

DO NOT FORGET TO SHUTDOWN YOUR CLUSTER (see below) (unless you think Amazon a worthy cause and wish to donate your extra cash to them).

Running the tests:
Open the file ~/.whirr/pigtest/hadoop-site.xml and find the line that has mapred.job.tracker. The next line should have the hostname that is running your Job Tracker. Copy that host name, but NOT the port numbers (ie the :nnnn where nnnn is 9001 or something similar). This value will be referred to as your_namenode.

cd your_path_to_pig_src
scp -i your_private_rsa_key_file test/e2e/pig/whirr/ your_namenode:~

if you have a patch you want to run
    scp -i your_private_rsa_key_file your_patch your_namenode:~

ssh -i your_private_rsa_key_file your_namenode

Now you can run whirr_test_patch to run some or all of the tests against trunk or against your patch. To run all the tests against trunk, do ./

To apply your patch and then run the tests, do ./ -p your_patch

To run just some of the tests, do ./ -t test_group_or_name where test_group_or_name is a test or group of tests you want to run. Multiple -t options can be passed.

whirr_test_patch is not idempotent. It downloads necessary packages, checks out trunk, applies your patch if appropriate, and generates the test data and loads into your cluster. Once you have successfully run it once, you should not run it again. If you wish to do additional testing cd src/trunk and run the end-to-end tests via ant as you normally would.

Initial setup takes around 5 minutes. Running all of the nightly tests currently (August 2011) takes about 10 hours. When you are just testing a patch for submission your are not expected to run the full suite of tests. Checkin, plus any tests you've added, plus all that cover the area of your change is sufficient.

Shutting down your cluster:
In the same shell you started the cluster:

./whirr destroy-cluster --config your_path_to_pig_trunk/test/e2e/pig/whirr/

How to Write an e2e Test

Writing a new e2e test does not require writing any new Java code (assuming you don't need to write a UDF for your job). The e2e test harness is written in Perl, and the tests are stored in .conf files, each of which is one big Perl hash (if you squint just right, it almost looks like JSON). These files are in test/e2e/pig/tests/. This hash is expected to have a groups key, which is an array. Each element in the array describes a collection of tests, usually oriented around a particular feature. For example the group FilterBoolean tests boolean predicates in filters. Every group in the array is a hash. It must have name and a tests keys. tests is expected to be an array of tests. Each test is again a hash, and must have a num, the test number and pig, the Pig Latin code to run. As an example look at the following, taken from nightly.conf:

$cfg = {
    'driver' => 'Pig',

    'groups' => [
            'name' => 'Checkin',
            'tests' => [
                    'num' => 1,
                    'pig' => q\a = load ':INPATH:/singlefile/studenttab10k' as (name, age, gpa);
                               store a into ':OUTPATH:';\,
                    'num' => 2,
                    'pig' => q\a = load ':INPATH:/singlefile/studenttab10k' as (name, age, gpa);
                               b = load ':INPATH:/singlefile/votertab10k' as (name, age, registration, contributions);
                               c = filter a by age < 50;
                               d = filter b by age < 50;
                               e = cogroup c by (name, age), d by (name, age) ;
                               f = foreach e generate flatten(c), flatten(d);
                               g = group f by registration;
                               h = foreach g generate group, SUM(f.d::contributions);
                               i = order h by $1;
                               store i into ':OUTPATH:';\,
                    'sortArgs' => ['-t', '  ', '+1', '-2'],
            'name' => 'LoaderPigStorageArg',
            'tests' => [
                    'num' => 1,
                    'pig' => q\a = load ':INPATH:/singlefile/studentcolon10k' using PigStorage(':') as (name, age, gpa);
                               store a into ':OUTPATH:';\,

This has two groups Checkin and LoaderPigStorageArg. Checkin has two tests.

In these simple cases the test harness runs the specified Pig Latin and generates a result. It then runs the same script against the version of Pig you specified as old (we are currently using Pig 0.8.1 in our nightly tests) and generates an expected result. These two results are then sorted and an md5 checksum taken. If this matches, the test is declared to have succeeded, otherwise, it failed.

For tests where sort order is important (as in Checkin_2 above), you can check that data is sorted using the Unix sort utility. This is done by passing an array of the arguments for sort. sort is then invoked before the harness sorts the data for comparison to the expected results to see if the data is sorted as specified. The sortArgs given above says to use tab as a delimiter and check that the output is sorted on the second (or first if you count from zero) field. See sort's man page for details.

For features that are new, you cannot test against old versions of Pig. For example, macros in 0.9 cannot be tested against 0.8.1. As an alternate to running the same Pig Latin script against an old version, you can run a different script. This script will be run using the current version, not the old one. To specify a different script, you need a key verify_pig_script. For example:

          # simple macro, no args
          'num' => 1,
          'pig' => q#define simple_macro() returns void {
                         a = load ':INPATH:/singlefile/studenttab10k' as (name, age, gpa);
                         b = foreach a generate age, name;
                         store b into ':OUTPATH:';

          'verify_pig_script' => q#a = load ':INPATH:/singlefile/studenttab10k' as (name, age, gpa);
                                   b = foreach a generate age, name;
                                   store b into ':OUTPATH:';#,

Some tests need to check that Pig outputs correct errors messages, returns correct codes, etc. These tests can define expected_err_regex, execpted_out_regex, not_expected_out_regex, not_expected_err_regex or rc. The first four search stderr or stdout for the provided regular expression (or lack thereof in the not cases). The last checks the return code against the provided value. Success or failure of the test is determined by whether these regular expressions or returns codes match. When these tags are present no expected results are generated via an old version of Pig or an alternate Pig Latin script.

An exhaustive list of keys supported in the test hash:


What it Does




Provides floatpostprocess with delimiter to use

'delimiter' => ':'

Only with flostpostprocess


This test will only be executed in specified mode; options are local and mapred

'execonly' => 'mapred'



Checks stderr error for the provided regular expression

'expected_err_regex' => "Out of bound access."



Checks stdout error for the provided regular expression

'expected_out_regex' => "A: {name: bytearray,age: bytearray,gpa: bytearray}"



Run floating point numbers through a post processor, since due to precision issues different runs of the same script will produce slightly different values. All floating point numbers are rounded to 3 decimal places. This must be used in conjunction with delimiter

'floatpostprocess' => 1

For outputs that include calculated floating point values.


Do not run this test, used when a test is failing but we don't want to remove it because it will be needed once the issue is fixed. A reason for ignoring the test should be given.

'ignore' => 'JIRA-19999'



Values to be passed on the pig command line before other Pig parameters; useful for passing properties.

'java_params' => ['-Dpig.cachedbag.memusage=0']



Checks that stderr does not match the provided regular expression

'not_expected_err_regex' => "ERROR"



Checks that stdout does not match the provided regular expression

'not_expected_out_regex' => "datafile"



Tells the test harness this is not a multi-query test; only necessary when a test has multiple store operators but should not be verified as if it were multi-query.

'notmq' => 1



Test number; must be unique in the test group

'num' => 1



The Pig Latin script to run in the test

q#a = load ':INPATH:/dir/studenttab10k' as (name, age, gpa); store a into ':OUTPATH:';#



Command line arguments to pass to pig when running this test.

'pig_params' => ['-p', qq(fname='studenttab10k')]



Expected return code

'rc' => 0



Arguments to pass to the Unix sort utility. When these are given, sort will be called before data is sorted for comparison with the expected results.

'sortArgs' => ['-t', ' ', '+0', '-1']

Only when job output should be sorted


Alternate Pig Latin script to use to generate the expected results

'verify_pig_script' => q\A = load ':INPATH:/singlefile/studenttab10k' as (name, age, gpa); store A into ':OUTPATH:';\,


Almost all test Pig Latin scripts need to make references to file paths. Rather than hardwire these paths in the tests, variables are provided. Whenever referencing paths in your scripts you should use these variables. The following table describes the most commonly used variables:


Used For



Location of test UDF jars constructed by the test harness

register :FUNCPATH:/testudf.jar;


Location where MapReduce jars used for testing the mapreduce operator are kept

b = mapreduce ':HADOOPHOME:/hadoop-examples.jar'


The path where Pig test data is stored

a = load ':INPATH:/singlefile/studenttab10k'


The path where Pig will write the results of a test

store a into ':OUTPATH:';


Location external script modules (e.g. Python) are kept

register ':SCRIPTHOMEPATH:/python/' using jython as myfuncs;


Temporary directory specific to a given test, can be used to store temporary files

pig_script = ":TMP:/script.pig"

The following files contain tests, and are located in test/e2e/pig/nightly:

conf File




larger size data

We keep these to a minimum as they take much longer than other tests.


Pig command line output (such as describe)



grunt operators, like ls



macro and import



multiquery scripts



negative conditions where Pig is expected to return an error



general positive tests

Your test goes here if it doesn't fit anywhere else

orc.confOrcStorage tests 


streaming feature



streaming feature in local mode



Pig scripts embedded in Python scripts


When writing new tests, if a group already exists that tests the functionality you are testing, add your tests to that group. There is a Regression group for tests that check bug fixes. If you are writing a new feature or writing tests for a previously un-tested feature, create a new group. When creating new groups, try to place it in an existing conf file that contains related tests. If you are creating a feature that will require many tests and multiple groups of tests, such as support for embedding Pig in a new language, create a new conf file for those tests.

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