The examples in this repository serve to demonstrate running Beam pipelines with SamzaRunner locally, in Yarn cluster, or in standalone cluster with Zookeeper. More complex pipelines can be built from here and run in similar manner.
The following examples are included:
WordCount reads a file as input (bounded data source), and computes word frequencies.
KafkaWordCount does the same word-count computation but reading from a Kafka stream (unbounded data source). It uses a fixed 10-sec window to aggregate the counts.
Each example can be run locally, in Yarn cluster or in standalone cluster. Here we use KafkaWordCount as an example.
Download and install JDK version 8. Verify that the JAVA_HOME environment variable is set and points to your JDK installation.
Check out the
$ git clone https://github.com/apache/samza-beam-examples.git $ cd samza-beam-examples
A script named “grid” is included in this project which allows you to easily download and install Zookeeper, Kafka, and Yarn. You can run the following to bring them all up running in your local machine:
$ scripts/grid bootstrap
All the downloaded package files will be put under
deploy folder. Once the grid command completes, you can verify that Yarn is up and running by going to http://localhost:8088. You can also choose to bring them up separately, e.g.:
$ scripts/grid install zookeeper $ scripts/grid start zookeeper
Now let's create a Kafka topic named “input-text” for this example:
$ ./deploy/kafka/bin/kafka-topics.sh --zookeeper localhost:2181 --create --topic input-text --partitions 10 --replication-factor 1
You can run directly within the project using maven:
$ mvn compile exec:java -Dexec.mainClass=org.apache.beam.examples.KafkaWordCount \ -Dexec.args="--runner=SamzaRunner --experiments=use_deprecated_read" -P samza-runner
To execute the example in either Yarn or standalone, you need to package it first. After packaging, we deploy and explode the tgz in the deploy folder:
$ mkdir -p deploy/examples $ mvn package && tar -xvf target/samza-beam-examples-0.1-dist.tar.gz -C deploy/examples/
You can use the
run-beam-standalone.sh script included in this repo to run an example in standalone mode. The config file is provided as
config/standalone.properties. Note by default we create one single split for the whole input (--maxSourceParallelism=1). To set each Kafka partition in a split, we can set a large “maxSourceParallelism” value which is the upper bound of the number of splits.
$ deploy/examples/bin/run-beam-standalone.sh org.apache.beam.examples.KafkaWordCount \ --configFilePath=$PWD/deploy/examples/config/standalone.properties --maxSourceParallelism=1024
Similar to running standalone, we can use the
run-beam-yarn.sh to run the examples in Yarn cluster. The config file is provided as
config/yarn.properties. To run the KafkaWordCount example in yarn:
$ deploy/examples/bin/run-beam-yarn.sh org.apache.beam.examples.KafkaWordCount \ --configFilePath=$PWD/deploy/examples/config/yarn.properties --maxSourceParallelism=1024
Now the pipeline is deployed to either locally, standalone or Yarn. Let's check out the results. First we start a kakfa consumer to listen to the output:
$ ./deploy/kafka/bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic word-count --property print.key=true
Then let's publish a few lines to the input Kafka topic:
$ ./deploy/kafka/bin/kafka-console-producer.sh --topic input-text --broker-list localhost:9092 Nory was a Catholic because her mother was a Catholic, and Nory’s mother was a Catholic because her father was a Catholic, and her father was a Catholic because his mother was a Catholic, or had been.
You should see the word count shows up in the consumer console in about 10 secs:
a 6 br 1 mother 3 was 6 Catholic 6 his 1 Nory 2 s 1 father 2 had 1 been 1 and 2 her 3 or 1 because 3
Feel free to build more complex pipelines based on the examples above, and reach out to us:
Subscribe and mail to email@example.com for any Beam questions.
Subscribe and mail to firstname.lastname@example.org for any Samza questions.