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commit 3617080e8347892e4d580e534d05a7ca05f29ab9
Author: Łukasz Gajowy <[email protected]>
AuthorDate: Thu Jun 7 18:46:27 2018 +0200

    [BEAM-4430] Improve Performance Testing Documentation
---
 src/documentation/io/testing.md | 223 ++++++++++++++++++++++++++++++++++++----
 1 file changed, 203 insertions(+), 20 deletions(-)

diff --git a/src/documentation/io/testing.md b/src/documentation/io/testing.md
index 020b879..7e212bc 100644
--- a/src/documentation/io/testing.md
+++ b/src/documentation/io/testing.md
@@ -147,9 +147,9 @@ However, when working locally, there is no requirement to 
use Kubernetes. All of
 ### Running integration tests {#running-integration-tests}
 
 The high level steps for running an integration test are:
-1.  Set up the data store corresponding to the test being run
-1.  Run the test, passing it connection info from the just created data store
-1.  Clean up the data store
+1.  Set up the data store corresponding to the test being run.
+1.  Run the test, passing it connection info from the just created data store.
+1.  Clean up the data store.
 
 Since setting up data stores and running the tests involves a number of steps, 
and we wish to time these tests when running performance benchmarks, we use 
PerfKit Benchmarker to manage the process end to end. With a single command, 
you can go from an empty Kubernetes cluster to a running integration test.
 
@@ -160,21 +160,28 @@ However, **PerfKit Benchmarker is not required for 
running integration tests**.
 
 Prerequisites:
 1.  [Install PerfKit 
Benchmarker](https://github.com/GoogleCloudPlatform/PerfKitBenchmarker)
-1.  Have a running Kubernetes cluster you can connect to locally using kubectl
+1.  Have a running Kubernetes cluster you can connect to locally using 
kubectl. We recommend using Google Kubernetes Engine - it's proven working for 
all the use cases we tested.  
 
-You won’t need to invoke PerfKit Benchmarker directly. Run `./gradlew 
performanceTest` in project's root directory, passing appropriate kubernetes 
scripts depending on the network you're using (local network or remote one).
+You won’t need to invoke PerfKit Benchmarker directly. Run `./gradlew 
performanceTest` task in project's root directory, passing kubernetes scripts 
of your choice (located in .test_infra/kubernetes directory). It will setup 
PerfKitBenchmarker for you.  
 
-Example run with the direct runner:
+Example run with the 
[Direct](https://beam.apache.org/documentation/runners/direct/) runner:
 ```
 ./gradlew performanceTest -DpkbLocation="/Users/me/PerfKitBenchmarker/pkb.py" 
-DintegrationTestPipelineOptions='["--numberOfRecords=1000"]' 
-DitModule=sdks/java/io/jdbc/ 
-DintegrationTest=org.apache.beam.sdk.io.jdbc.JdbcIOIT 
-DkubernetesScripts="/Users/me/beam/.test-infra/kubernetes/postgres/postgres-service-for-local-dev.yml"
 
-DbeamITOptions="/Users/me/beam/.test-infra/kubernetes/postgres/pkb-config-local.yml"
 -DintegrationTestRunner=direct
 ```
 
 
-Example run with the Cloud Dataflow runner:
+Example run with the [Google Cloud 
Dataflow](https://beam.apache.org/documentation/runners/dataflow/) runner:
 ```
-/gradlew performanceTest -DpkbLocation="/Users/me/PerfKitBenchmarker/pkb.py" 
-DintegrationTestPipelineOptions='["--numberOfRecords=1000", 
"--project=GOOGLE_CLOUD_PROJECT", "--tempRoot=GOOGLE_STORAGE_BUCKET"]' 
-DitModule=sdks/java/io/jdbc/ 
-DintegrationTest=org.apache.beam.sdk.io.jdbc.JdbcIOIT 
-DkubernetesScripts="/Users/me/beam/.test-infra/kubernetes/postgres/postgres-service-for-local-dev.yml"
 
-DbeamITOptions="/Users/me/beam/.test-infra/kubernetes/postgres/pkb-config-local.yml"
 -Dintegr [...]
+./gradlew performanceTest -DpkbLocation="/Users/me/PerfKitBenchmarker/pkb.py" 
-DintegrationTestPipelineOptions='["--numberOfRecords=1000", 
"--project=GOOGLE_CLOUD_PROJECT", "--tempRoot=GOOGLE_STORAGE_BUCKET"]' 
-DitModule=sdks/java/io/jdbc/ 
-DintegrationTest=org.apache.beam.sdk.io.jdbc.JdbcIOIT 
-DkubernetesScripts="/Users/me/beam/.test-infra/kubernetes/postgres/postgres-service-for-local-dev.yml"
 
-DbeamITOptions="/Users/me/beam/.test-infra/kubernetes/postgres/pkb-config-local.yml"
 -Dinteg [...]
 ```
 
+Example run with the HDFS filesystem and Cloud Dataflow runner:
+
+```
+./gradlew performanceTest -DpkbLocation="/Users/me/PerfKitBenchmarker/pkb.py" 
-DintegrationTestPipelineOptions='["--numberOfRecords=100000", 
"--project=GOOGLE_CLOUD_PROJECT", "--tempRoot=GOOGLE_STORAGE_BUCKET"]' 
-DitModule=sdks/java/io/file-based-io-tests/ 
-DintegrationTest=org.apache.beam.sdk.io.text.TextIOIT 
-DkubernetesScripts=".test-infra/kubernetes/hadoop/LargeITCluster/hdfs-multi-datanode-cluster.yml,.test-infra/kubernetes/hadoop/LargeITCluster/hdfs-multi-datanode-cluster-for-local
 [...]
+```
+
+NOTE: When using Direct runner along with HDFS cluster, please set `export 
HADOOP_USER_NAME=root` before runnning `performanceTest` task.
 
 Parameter descriptions:
 
@@ -200,7 +207,7 @@ Parameter descriptions:
     <tr>
      <td>-DintegrationTestPipelineOptions
      </td>
-     <td>Passes pipeline options directly to the test being run.
+     <td>Passes pipeline options directly to the test being run. Note that 
some pipeline options may be runner specific (like "--project" or 
"--tempRoot"). 
      </td>
     </tr>
     <tr>
@@ -212,7 +219,7 @@ Parameter descriptions:
     <tr>
      <td>-DintegrationTest
      </td>
-     <td>Specifies the test to be run.
+     <td>Specifies the test to be run (fully qualified reference to class/test 
method).
      </td>
     </tr>
     <tr>
@@ -233,31 +240,209 @@ Parameter descriptions:
       <td>Runner to be used for running the test. Currently possible options 
are: direct, dataflow.
       </td>
     </tr>
+    <tr>
+      <td>-DbeamExtraProperties
+      </td>
+      <td>Any other "extra properties" to be passed to Gradle, eg. 
"'[filesystem=hdfs]'". 
+      </td>
+    </tr>
   </tbody>
 </table>
 
-
-
 #### Without PerfKit Benchmarker {#without-perfkit-benchmarker}
 
-If you're using Kubernetes, make sure you can connect to your cluster locally 
using kubectl. Otherwise, skip to step 3 below.
+If you're using Kubernetes scripts to host data stores, make sure you can 
connect to your cluster locally using kubectl. If you have your own data stores 
already setup, you just need to execute step 3 from below list.
 
 1.  Set up the data store corresponding to the test you wish to run. You can 
find Kubernetes scripts for all currently supported data stores in 
[.test-infra/kubernetes](https://github.com/apache/beam/tree/master/.test-infra/kubernetes).
     1.  In some cases, there is a setup script (*.sh). In other cases, you can 
just run ``kubectl create -f [scriptname]`` to create the data store.
     1.  Convention dictates there will be:
-        1.  A core yml script for the data store itself, plus a `NodePort` 
service. The `NodePort` service opens a port to the data store for anyone who 
connects to the Kubernetes cluster's machines.
-        1.  A separate script, called for-local-dev, which sets up a 
LoadBalancer service.
+        1.  A yml script for the data store itself, plus a `NodePort` service. 
The `NodePort` service opens a port to the data store for anyone who connects 
to the Kubernetes cluster's machines from within same subnetwork. Such scripts 
are typically useful when running the scripts on Minikube Kubernetes Engine.
+        1.  A separate script, with LoadBalancer service. Such service will 
expose an _external ip_ for the datastore. Such scripts are needed when 
external access is required (eg. on Jenkins). 
     1.  Examples:
         1.  For JDBC, you can set up Postgres: `kubectl create -f 
.test-infra/kubernetes/postgres/postgres.yml`
         1.  For Elasticsearch, you can run the setup script: `bash 
.test-infra/kubernetes/elasticsearch/setup.sh`
 1.  Determine the IP address of the service:
     1.  NodePort service: `kubectl get pods -l 'component=elasticsearch' -o 
jsonpath={.items[0].status.podIP}`
     1.  LoadBalancer service:` kubectl get svc elasticsearch-external -o 
jsonpath='{.status.loadBalancer.ingress[0].ip}'`
-1.  Run the test using the instructions in the class (e.g. see the 
instructions in JdbcIOIT.java)
+1.  Run the test using `integrationTest` gradle task and the instructions in 
the test class (e.g. see the instructions in JdbcIOIT.java).
 1.  Tell Kubernetes to delete the resources specified in the Kubernetes 
scripts:
     1.  JDBC: `kubectl delete -f .test-infra/kubernetes/postgres/postgres.yml`
     1.  Elasticsearch: `bash .test-infra/kubernetes/elasticsearch/teardown.sh`
 
+##### integrationTest Task {#integration-test-task}
+
+Since `performanceTest` task involved running PerfkitBenchmarker, we can't use 
it to run the tests manually. For such purposes a more "low-level" task called 
`integrationTest` was introduced.  
+
+
+Example usage on Cloud Dataflow runner: 
+
+```
+./gradlew integrationTest -p sdks/java/io/hadoop-input-format 
-DintegrationTestPipelineOptions='["--project=GOOGLE_CLOUD_PROJECT", 
"--tempRoot=GOOGLE_STORAGE_BUCKET", "--numberOfRecords=1000", 
"--postgresPort=5432", "--postgresServerName=SERVER_NAME", 
"--postgresUsername=postgres", "--postgresPassword=PASSWORD", 
"--postgresDatabaseName=postgres", "--postgresSsl=false", 
"--runner=TestDataflowRunner"]' -DintegrationTestRunner=dataflow 
--tests=org.apache.beam.sdk.io.hadoop.inputformat.Hadoo [...]
+```
+
+Example usage on HDFS filesystem and Direct runner: 
+
+NOTE: Below setup will only work when /etc/hosts file contains entries with 
hadoop namenode and hadoop datanodes external IPs. Please see explanation in: 
[Small Cluster config 
file](https://github.com/apache/beam/blob/master/.test-infra/kubernetes/hadoop/SmallITCluster/pkb-config.yml)
 and [Large Cluster config 
file](https://github.com/apache/beam/blob/master/.test-infra/kubernetes/hadoop/LargeITCluster/pkb-config.yml).
+
+```
+export HADOOP_USER_NAME=root 
+
+./gradlew integrationTest -p sdks/java/io/file-based-io-tests 
-DintegrationTestPipelineOptions='["--numberOfRecords=1000", 
"--filenamePrefix=hdfs://HDFS_NAMENODE:9000/XMLIOIT", 
"--hdfsConfiguration=[{\"fs.defaultFS\":\"hdfs://HDFS_NAMENODE:9000\",\"dfs.replication\":1,\"dfs.client.use.datanode.hostname\":\"true\"
 }]" ]' -DintegrationTestRunner=direct -Dfilesystem=hdfs --tests 
org.apache.beam.sdk.io.xml.XmlIOIT
+```
+
+Parameter descriptions:
+
+
+<table class="table">
+  <thead>
+    <tr>
+     <td>
+      <strong>Option</strong>
+     </td>
+     <td>
+       <strong>Function</strong>
+     </td>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+     <td>-p sdks/java/io/file-based-io-tests/
+     </td>
+     <td>Specifies the project submodule of the I/O to test.
+     </td>
+    </tr>
+    <tr>
+     <td>-DintegrationTestPipelineOptions
+     </td>
+     <td>Passes pipeline options directly to the test being run.
+     </td>
+    </tr>
+    <tr>
+     <td>-DintegrationTestRunner
+     </td>
+     <td>Runner to be used for running the test. Currently possible options 
are: direct, dataflow.
+     </td>
+    </tr>
+    <tr>
+     <td>-Dfilesystem
+     </td>
+     <td>(optional, where applicable) Filesystem to be used to run the test. 
Currently possible options are: gcs, hdfs, s3. If not provided, local 
filesystem will be used. 
+     </td>
+    </tr>
+    <tr>
+     <td>--tests
+     </td>
+     <td>Specifies the test to be run (fully qualified reference to class/test 
method). 
+     </td>
+    </tr>
+  </tbody>
+</table>
+
+#### Running Integration Tests on Pull Requests {#running-on-pull-requests}
+
+Thanks to [ghprb](https://github.com/janinko/ghprb) plugin it is possible to 
run Jenkins jobs when specific phrase is typed in a Github Pull Request's 
comment. Integration tests that have Jenkins job defined can be triggered this 
way. You can run integration tests using these phrases:
+
+<table class="table">
+  <thead>
+    <tr>
+     <td>
+      <strong>Test</strong>
+     </td>
+     <td>
+       <strong>Phrase</strong>
+     </td>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+     <td>JdbcIOIT
+     </td>
+     <td>Run Java JdbcIO Performance Test
+     </td>
+    </tr>
+    <tr>
+     <td>MongoDBIOIT
+     </td>
+     <td>Run Java MongoDBIO Performance Test
+     </td>
+    </tr>
+    <tr>
+     <td>HadoopInputFormatIOIT
+     </td>
+     <td>Run Java HadoopInputFormatIO Performance Test
+     </td>
+    </tr>
+    <tr>
+     <td>TextIO - local filesystem
+     </td>
+     <td>Run Java TextIO Performance Test 
+     </td>
+    </tr>
+    <tr>
+     <td>TextIO - HDFS
+     </td>
+     <td>Run Java TextIO Performance Test HDFS 
+     </td>
+    </tr>
+    <tr>
+     <td>Compressed TextIO - local filesystem
+     </td>
+     <td>Run Java CompressedTextIO Performance Test 
+     </td>
+    </tr>
+    <tr>
+     <td>Compressed TextIO - HDFS
+     </td>
+     <td>Run Java CompressedTextIO Performance Test HDFS 
+     </td>
+    </tr>
+    <tr>
+     <td>AvroIO - local filesystem
+     </td>
+     <td>Run Java AvroIO Performance Test 
+     </td>
+    </tr>
+    <tr>
+     <td>AvroIO - HDFS
+     </td>
+     <td>Run Java AvroIO Performance Test HDFS 
+     </td>
+    </tr>
+    <tr>
+     <td>TFRecordIO - local filesystem
+     </td>
+     <td>Run Java TFRecordIO Performance Test 
+     </td>
+    </tr>
+    <tr>
+     <td>ParquetIO - local filesystem
+     </td>
+     <td>Run Java ParquetIO Performance Test 
+     </td>
+    </tr>
+    <tr>
+     <td>XmlIO - local filesystem
+     </td>
+     <td>Run Java XmlIO Performance Test 
+     </td>
+    </tr>
+    <tr>
+     <td>XmlIO - HDFS
+     </td>
+     <td>Run Java XmlIO Performance Test on HDFS
+     </td>
+    </tr>
+  </tbody>
+</table>
+
+Every job definition can be found in 
[.test-infra/jenkins](https://github.com/apache/beam/tree/master/.test-infra/jenkins).
 
+If you modified/added new Jenkins job definitions in your Pull Request, run 
the seed job before running the integration test (comment: "Run seed job").
+
+### Performance testing dashboard {#performance-testing-dashboard}
+
+We measure the performance of IOITs by gathering test execution times from 
Jenkins jobs that run periodically. The consequent results are stored in a 
database (BigQuery), therefore we can display them in a form of plots. 
+
+The dashboard gathering all the results is available here: [Performance 
Testing 
Dashboard](https://apache-beam-testing.appspot.com/explore?dashboard=5755685136498688)
 
 ### Implementing Integration Tests {#implementing-integration-tests}
 
@@ -268,7 +453,6 @@ There are three components necessary to implement an 
integration test:
 
 These three pieces are discussed in detail below.
 
-
 #### Test Code {#test-code}
 
 These are the conventions used by integration testing code:
@@ -295,12 +479,11 @@ As discussed in [Integration tests, data stores, and 
Kubernetes](#integration-te
 If you would like help with this or have other questions, contact the Beam 
dev@ mailing list and the community may be able to assist you.
 
 Guidelines for creating a Beam data store Kubernetes script:
-1.  **You must only provide access to the data store instance via a `NodePort` 
service.**
-    *   This is a requirement for security, since it means that only the local 
network has access to the data store. This is particularly important since many 
data stores don't have security on by default, and even if they do, their 
passwords will be checked in to our public Github repo.
+
 1.  **You should define two Kubernetes scripts.**
     *   This is the best known way to implement item #1.
     *   The first script will contain the main datastore instance script 
(`StatefulSet`) plus a `NodePort` service exposing the data store. This will be 
the script run by the Beam Jenkins continuous integration server.
-    *   The second script will define a `LoadBalancer` service, used for local 
development if the Kubernetes cluster is on another network. This file's name 
is usually suffixed with '-for-local-dev'.
+    *   The second script will define an additional `LoadBalancer` service, 
used to expose an external IP address to the data store if the Kubernetes 
cluster is on another network. This file's name is usually suffixed with 
'-for-local-dev'.
 1.  **You must ensure that pods are recreated after crashes.**
     *   If you use a `pod` directly, it will not be recreated if the pod 
crashes or something causes the cluster to move the container for your pod.
     *   In most cases, you'll want to use `StatefulSet` as it supports 
persistent disks that last between restarts, and having a stable network 
identifier associated with the pod using a particular persistent disk. 
`Deployment` and `ReplicaSet` are also possibly useful, but likely in fewer 
scenarios since they do not have those features.

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