commit	2b2286fe10de562e8b42b515d523c1fbf26b4177	[log] [tgz]
author	Antonio Barone <syntonyze@gmail.com>	Fri Jan 11 17:44:24 2019 +0000
committer	Antonio Barone <syntonyze@gmail.com>	Fri Jan 11 17:44:24 2019 +0000
tree	0e30d162181dda9b3f99ddd8a5b639b550cbd47c
parent	72e55421732a32b4be227e6d2f2a232cbf8020c7 [diff]

tree: 0e30d162181dda9b3f99ddd8a5b639b550cbd47c

README.md

Intro

This repository provides a set of spark ETL jobs able to extract, transform and persist data from gerrit projects with the purpose of performing analytics tasks.

Each job focuses on a specific dataset and it knows how to extract it, filter it, aggregate it, transform it and then persist it.

The persistent storage of choice is elasticsearch, which plays very well with the kibana dashboard for visualizing the analytics.

All jobs are configured as separate sbt projects and have in common just a thin layer of core dependencies, such as spark, elasticsearch client, test utils, etc.

Each job can be built and published independently, both as a fat jar artifact or a docker image.

Spark ETL jobs

Here below an exhaustive list of all the spark jobs provided by this repo, along with their documentation.

Git Commits

Extracts and aggregates git commits data from Gerrit Projects.

Requires a Gerrit 2.13.x or later with the analytics plugin installed and Apache Spark 2.11 or later.

Job can be launched with the following parameters:

bin/spark-submit \
    --class com.gerritforge.analytics.gitcommits.job.Main \
    --conf spark.es.nodes=es.mycompany.com \
    $JARS/analytics-etl-gitcommits.jar \
    --since 2000-06-01 \
    --aggregate email_hour \
    --url http://gerrit.mycompany.com \
    -e gerrit \
    --username gerrit-api-username \
    --password gerrit-api-password

You can also run this job in docker:

docker run -ti --rm \
    -e ES_HOST="es.mycompany.com" \
    -e GERRIT_URL="http://gerrit.mycompany.com" \
    -e ANALYTICS_ARGS="--since 2000-06-01 --aggregate email_hour -e gerrit" \
    gerritforge/gerrit-analytics-etl-gitcommits:latest

Parameters

since, until, aggregate are the same defined in Gerrit Analytics plugin see: https://gerrit.googlesource.com/plugins/analytics/+/master/README.md
-u --url Gerrit server URL with the analytics plugins installed
-p --prefix (optional) Projects prefix. Limit the results to those projects that start with the specified prefix.
-e --elasticIndex Elastic Search index name. If not provided no ES export will be performed
-o --out folder location for storing the output as JSON files if not provided data is saved to /analytics- where is the system temporary directory
-a --email-aliases (optional) “emails to author alias” input data path.
-k --ignore-ssl-cert allows to proceed even for server connections otherwise considered insecure.
CSVs with 3 columns are expected in input.
Here an example of the required files structure:
```
author,email,organization
John Smith,john@email.com,John's Company
John Smith,john@anotheremail.com,John's Company
David Smith,david.smith@email.com,Indipendent
David Smith,david@myemail.com,Indipendent
```
You can use the following command to quickly extract the list of authors and emails to create part of an input CSV file:
```
echo -e "author,email\n$(git log --pretty="%an,%ae%n%cn,%ce"|sort |uniq )" > /tmp/my_aliases.csv
```
Once you have it, you just have to add the organization column.
NOTE:
- organization will be extracted from the committer email if not specified
- author will be defaulted to the committer name if not specified

Build

JAR

To build the jar file, simply use

sbt analyticsETLGitCommits/assembly

Docker

To build the gerritforge/gerrit-analytics-etl-gitcommits docker container just run:

sbt analyticsETLGitCommits/docker.

If you want to distribute use:

sbt analyticsETLGitCommits/dockerBuildAndPush.

The build and distribution override the latest image tag too Remember to create an annotated tag for a release. The tag is used to define the docker image tag too

Audit Logs

Extract, aggregate and persist auditLog entries produced by Gerrit via the audit-sl4j plugin. AuditLog entries are an immutable trace of what happened on Gerrit and this ETL can leverage that to answer questions such as:

How is GIT incoming traffic distributed?
Git/SSH vs. Git/HTTP traffic
Git receive-pack vs. upload-pack
Top#10 users of receive-pack

and many others questions related to the usage of Gerrit.

Job can be launched, for example, with the following parameters:

spark-submit \
    --class com.gerritforge.analytics.auditlog.job.Main \
    --conf spark.es.nodes=es.mycompany.com \
    --conf spark.es.port=9200 \
    --conf spark.es.index.auto.create=true \
    $JARS/analytics-etl-auditlog.jar \
        --gerritUrl https://gerrit.mycompany.com \
        --elasticSearchIndex gerrit \
        --eventsPath /path/to/auditlogs \
        --ignoreSSLCert false \
        --since 2000-06-01 \
        --until 2020-12-01

You can also run this job in docker:

docker run \
    --volume <source>/audit_log:/app/events/audit_log -ti --rm \
    -e ES_HOST="<elasticsearch_url>" \
    -e GERRIT_URL="http://<gerrit_url>:<gerrit_port>" \
    -e ANALYTICS_ARGS="--elasticSearchIndex gerrit --eventsPath /app/events/audit_log --ignoreSSLCert false --since 2000-06-01 --until 2020-12-01 -a hour" \
    gerritforge/gerrit-analytics-etl-auditlog:latest

Parameters

-u, --gerritUrl - gerrit server URL (Required)
--username - Gerrit API Username (Optional)
--password - Gerrit API Password (Optional)
-i, --elasticSearchIndex - elasticSearch index to persist data into (Required)
-p, --eventsPath - path to a directory (or a file) containing auditLogs events. Supports also .gz files. (Required)
-a, --eventsTimeAggregation - Events of the same type, produced by the same user will be aggregated with this time granularity: ‘second’, ‘minute’, ‘hour’, ‘week’, ‘month’, ‘quarter’. (Optional) - Default: ‘hour’
-k, --ignoreSSLCert - Ignore SSL certificate validation (Optional) - Default: false
-s, --since - process only auditLogs occurred after (and including) this date (Optional)
-u, --until - process only auditLogs occurred before (and including) this date (Optional)
-a, --additionalUserInfoPath - path to a CSV file containing additional user information (Optional). Currently it is only possible to add user type (i.e.: bot, human). If the type is not specified the user will be considered human.
Here an additional user information CSV file example:
```
  id,type
  123,"bot"
  456,"bot"
  789,"human"
```

Build

JAR

To build the jar file, simply use

sbt analyticsETLAuditLog/assembly

Docker

To build the gerritforge/gerrit-analytics-etl-auditlog docker image just run:

sbt analyticsETLAuditLog/docker.

If you want to distribute it use:

sbt analyticsETLAuditLog/dockerBuildAndPush.

The build and distribution override the latest image tag too.

Development environment

A docker compose file is provided to spin up an instance of Elastisearch with Kibana locally. Just run docker-compose up.

Caveats

If you want to run the git ETL job from within docker against containerized elasticsearch and/or gerrit instances, you need to make them reachable by the ETL container. You can do this by spinning the ETL within the same network used by your elasticsearch/gerrit container (use --network argument)

If elasticsearch or gerrit run on your host machine, then you need to make that reachable by the ETL container. You can do this by providing routing to the docker host machine (i.e. --add-host="gerrit:<your_host_ip_address>" --add-host="elasticsearch:<your_host_ip_address>")

For example:

Run gitcommits ETL:

HOST_IP=`ifconfig en0 | grep "inet " | awk '{print $2}'` \
    docker run -ti --rm \
        --add-host="gerrit:$HOST_IP" \
        --network analytics-etl_ek \
        -e ES_HOST="elasticsearch" \
        -e GERRIT_URL="http://$HOST_IP:8080" \
        -e ANALYTICS_ARGS="--since 2000-06-01 --aggregate email_hour -e gerrit" \
        gerritforge/gerrit-analytics-etl-gitcommits:latest

Run auditlog ETL:

HOST_IP=`ifconfig en0 | grep "inet " | awk '{print $2}'` \
    docker run -ti --rm --volume <source>/audit_log:/app/events/audit_log \
    --add-host="gerrit:$HOST_IP" \
    --network analytics-wizard_ek \
    -e ES_HOST="elasticsearch" \
    -e GERRIT_URL="http://$HOST_IP:8181" \
    -e ANALYTICS_ARGS="--elasticSearchIndex gerrit --eventsPath /app/events/audit_log --ignoreSSLCert true --since 2000-06-01 --until 2020-12-01 -a hour" \
    gerritforge/gerrit-analytics-etl-auditlog:latest

If Elastisearch dies with exit code 137 you might have to give Docker more memory (check this article for more details)
Should ElasticSearch need authentication (i.e.: if X-Pack is enabled), credentials can be passed through the spark.es.net.http.auth.pass and spark.es.net.http.auth.user parameters.
If the dockerized spark job cannot connect to elasticsearch (also, running on docker) you might need to tell elasticsearch to publish the host to the cluster using the _site_ address.

elasticsearch:
    ...
    environment:
       ...
      - http.host=0.0.0.0
      - network.host=_site_
      - http.publish_host=_site_
      ...

See here for more info

Build all

To perform actions across all jobs simply run the relevant sbt task without specifying the job name. For example:

Test all jobs: sbt test
Build jar for all jobs: sbt assembly
Build docker for all jobs: sbt docker