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# Purpose: Amazon EMR Serverless and Amazon MSK Serverless Demo
# Write messages from a CSV file to Kafka topicC
# to simulate real-time streaming sales data
# Author: Gary A. Stafford
# Date: 2022-07-27
# Note: Requires --bootstrap_servers and --s3_bucket arguments
import argparse
import time
import pyspark.sql.functions as F
from pyspark.sql import SparkSession
from pyspark.sql.types import StructField, StructType, IntegerType, \
StringType, FloatType
def main():
args = parse_args()
spark = SparkSession \
.builder \
.appName("04-stream-sales-to-kafka") \
.getOrCreate()
spark.sparkContext.setLogLevel("INFO")
schema = StructType([
StructField("payment_id", IntegerType(), False),
StructField("customer_id", IntegerType(), False),
StructField("amount", FloatType(), False),
StructField("payment_date", StringType(), False),
StructField("city", StringType(), True),
StructField("district", StringType(), True),
StructField("country", StringType(), False),
])
df_sales = read_from_csv(spark, schema, args)
df_sales.cache()
write_to_kafka(spark, df_sales, args)
def read_from_csv(spark, schema, args):
df_sales = spark.read \
.csv(path=f"s3a://{args.s3_bucket}/sample_data/{args.sample_data_file}",
schema=schema, header=True, sep="|")
return df_sales
def write_to_kafka(spark, df_sales, args):
options_write = {
"kafka.bootstrap.servers":
args.bootstrap_servers,
"topic":
args.write_topic,
"kafka.security.protocol":
"SASL_SSL",
"kafka.sasl.mechanism":
"AWS_MSK_IAM",
"kafka.sasl.jaas.config":
"software.amazon.msk.auth.iam.IAMLoginModule required;",
"kafka.sasl.client.callback.handler.class":
"software.amazon.msk.auth.iam.IAMClientCallbackHandler"
}
sales_count = df_sales.count()
for r in range(0, sales_count):
row = df_sales.collect()[r]
df_message = spark.createDataFrame([row], df_sales.schema)
df_message = df_message \
.drop("payment_date") \
.withColumn("payment_date", F.current_timestamp())
df_message \
.selectExpr("CAST(payment_id AS STRING) AS key",
"to_json(struct(*)) AS value") \
.write \
.format("kafka") \
.options(**options_write) \
.save()
df_message.show(1)
time.sleep(args.message_delay)
def parse_args():
"""Parse argument values from command-line"""
parser = argparse.ArgumentParser(description="Arguments required for script.")
parser.add_argument("--bootstrap_servers", required=True, help="Kafka bootstrap servers")
parser.add_argument("--s3_bucket", required=True, help="Amazon S3 bucket")
parser.add_argument("--write_topic", default="topicC", required=False, help="Kafka topic to write to")
parser.add_argument("--sample_data_file", default="sales_incremental_large.csv", required=False, help="data file")
parser.add_argument("--message_delay", default=0.5, required=False, help="message publishing delay")
args = parser.parse_args()
return args
if __name__ == "__main__":
main()
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