Spark Structured Streaming Sample Project (Python)

Sample Code

The following code snippets are used as an example. For complete codes, see SecurityKafkaWordCount.

When new data is available in Streaming DataFrame/Dataset, outputMode is used for configuring data written to the Streaming receptor.

#!/usr/bin/python
# -*- coding: utf-8 -*-

import sys
from pyspark.sql import SparkSession
from pyspark.sql.functions import explode, split

if __name__ == "__main__":
    if len(sys.argv) < 3:
        print("Usage: <bootstrapServers> <subscribeType> <topics>")
        exit(-1)

    bootstrapServers = sys.argv[1]
    subscribeType = sys.argv[2]
    topics = sys.argv[3]

    # Initialize SparkSession.
    spark = SparkSession.builder.appName("KafkaWordCount").getOrCreate()

    # Create the DataFrame of input lines stream from Kafka.
	# In security mode, set spark/conf/jaas.conf and jaas-zk.conf to KafkaClient.
    lines = spark.readStream.format("kafka")\
    .option("kafka.bootstrap.servers", bootstrapServers)\
    .option(subscribeType, topics)\
    .load()\
    .selectExpr("CAST(value AS STRING)")


    # Split lines into words.
    words = lines.select(explode(split(lines.value, " ")).alias("word"))
    # Generate the running word count.
    wordCounts = words.groupBy("word").count()

    # Start to query whether the running counts are printed to the console.
    query = wordCounts.writeStream\
    .outputMode("complete")\
    .format("console")\
    .start()

    query.awaitTermination()