5.5 KiB
Nomad / Spark integration
Spark supports using a Nomad cluster to run Spark applications. When running on Nomad, the Spark executors that run Spark tasks for your application, and optionally the application driver itself, run as Nomad tasks in a Nomad job. See the usage guide for more details.
To give the Spark integration a test drive cd
to examples/spark/spark
on one of the servers (the examples/spark/spark
subdirectory will be created when the cluster is provisioned).
A number of sample Spark commands are listed below. These demonstrate some of the official examples as well as features like spark-sql, spark-shell and dataframes.
You can monitor Nomad status simulaneously with:
$ nomad status
$ nomad status [JOB_ID]
$ nomad alloc-status [ALLOC_ID]
Sample Spark commands
SparkPi
Java (client mode)
$ ./bin/spark-submit --class org.apache.spark.examples.JavaSparkPi --master nomad --conf spark.executor.instances=8 --conf spark.nomad.sparkDistribution=https://s3.amazonaws.com/rcgenova-nomad-spark/spark-2.1.0-bin-nomad-preview-6.tgz examples/jars/spark-examples*.jar 100
Java (cluster mode)
./bin/spark-submit --class org.apache.spark.examples.JavaSparkPi --master nomad --deploy-mode cluster --conf spark.executor.instances=4 --conf spark.nomad.cluster.monitorUntil=complete --conf spark.nomad.sparkDistribution=https://s3.amazonaws.com/rcgenova-nomad-spark/spark-2.1.0-bin-nomad-preview-6.tgz https://s3.amazonaws.com/rcgenova-nomad-spark/spark-examples_2.11-2.1.0-SNAPSHOT.jar 100
Python (client mode)
$ ./bin/spark-submit --master nomad --conf spark.executor.instances=8 --conf spark.nomad.sparkDistribution=https://s3.amazonaws.com/rcgenova-nomad-spark/spark-2.1.0-bin-nomad-preview-6.tgz examples/src/main/python/pi.py 100
Python (cluster mode)
./bin/spark-submit --master nomad --deploy-mode cluster --conf spark.executor.instances=4 --conf spark.nomad.cluster.monitorUntil=complete --conf spark.nomad.sparkDistribution=https://s3.amazonaws.com/rcgenova-nomad-spark/spark-2.1.0-bin-nomad-preview-6.tgz examples/src/main/python/pi.py 100
Scala, (client mode)
$ ./bin/spark-submit --class org.apache.spark.examples.SparkPi --master nomad --conf spark.executor.instances=8 --conf spark.nomad.sparkDistribution=https://s3.amazonaws.com/rcgenova-nomad-spark/spark-2.1.0-bin-nomad-preview-6.tgz examples/jars/spark-examples*.jar 100
Machine Learning
Python (client mode)
$ ./bin/spark-submit --master nomad --conf spark.executor.instances=8 --conf spark.nomad.sparkDistribution=https://s3.amazonaws.com/rcgenova-nomad-spark/spark-2.1.0-bin-nomad-preview-6.tgz examples/src/main/python/ml/logistic_regression_with_elastic_net.py
Scala (client mode)
$ ./bin/spark-submit --class org.apache.spark.examples.SparkLR --master nomad --conf spark.executor.instances=8 --conf spark.nomad.sparkDistribution=https://s3.amazonaws.com/rcgenova-nomad-spark/spark-2.1.0-bin-nomad-preview-6.tgz examples/jars/spark-examples*.jar
Streaming
Run these commands simultaneously:
bin/spark-submit --class org.apache.spark.examples.streaming.clickstream.PageViewGenerator --master nomad --deploy-mode cluster --conf spark.executor.instances=4 --conf spark.nomad.cluster.monitorUntil=complete --conf spark.nomad.sparkDistribution=https://s3.amazonaws.com/rcgenova-nomad-spark/spark-2.1.0-bin-nomad-preview-6.tgz https://s3.amazonaws.com/rcgenova-nomad-spark/spark-examples_2.11-2.1.0-SNAPSHOT.jar 44444 10
bin/spark-submit --class org.apache.spark.examples.streaming.clickstream.PageViewStream --master nomad --deploy-mode cluster --conf spark.executor.instances=4 --conf spark.nomad.cluster.monitorUntil=complete --conf spark.nomad.sparkDistribution=https://s3.amazonaws.com/rcgenova-nomad-spark/spark-2.1.0-bin-nomad-preview-6.tgz https://s3.amazonaws.com/rcgenova-nomad-spark/spark-examples_2.11-2.1.0-SNAPSHOT.jar errorRatePerZipCode localhost 44444
pyspark
$ ./bin/pyspark --master nomad --conf spark.executor.instances=8 --conf spark.nomad.sparkDistribution=https://s3.amazonaws.com/rcgenova-nomad-spark/spark-2.1.0-bin-nomad-preview-6.tgz
df = spark.read.json("examples/src/main/resources/people.json")
df.show()
df.printSchema()
df.createOrReplaceTempView("people")
sqlDF = spark.sql("SELECT * FROM people")
sqlDF.show()
spark-shell
$ ./bin/spark-shell --master nomad --conf spark.executor.instances=8 --conf spark.nomad.sparkDistribution=https://s3.amazonaws.com/rcgenova-nomad-spark/spark-2.1.0-bin-nomad-preview-6.tgz
From spark-shell:
:type spark
spark.version
val data = 1 to 10000
val distData = sc.parallelize(data)
distData.filter(_ < 10).collect()
spark-sql
bin/spark-sql --master nomad --conf spark.executor.instances=8 --conf spark.nomad.sparkDistribution=https://s3.amazonaws.com/rcgenova-nomad-spark/spark-2.1.0-bin-nomad-preview-6.tgz jars/spark-sql_2.11-2.1.0-SNAPSHOT.jar
From spark-shell:
CREATE TEMPORARY VIEW usersTable
USING org.apache.spark.sql.parquet
OPTIONS (
path "examples/src/main/resources/users.parquet"
);
SELECT * FROM usersTable;
Data frames
bin/spark-shell --master nomad --conf spark.executor.instances=8 --conf spark.nomad.sparkDistribution=https://s3.amazonaws.com/rcgenova-nomad-spark/spark-2.1.0-bin-nomad-preview-6.tgz
From spark-shell:
val usersDF = spark.read.load("examples/src/main/resources/users.parquet")
usersDF.select("name", "favorite_color").write.save("/tmp/namesAndFavColors.parquet")