Spark SQL Streaming Amazon SQS Data Source

A library for reading data from Amzon S3 with optimised listing using Amazon SQS using Spark SQL Streaming ( or Structured streaming.).

Linking

Using SBT:

libraryDependencies += "org.apache.bahir" %% "spark-sql-streaming-sqs" % "{{site.SPARK_VERSION}}"

Using Maven:

<dependency>
    <groupId>org.apache.bahir</groupId>
    <artifactId>spark-sql-streaming-sqs_{{site.SCALA_BINARY_VERSION}}</artifactId>
    <version>{{site.SPARK_VERSION}}</version>
</dependency>

This library can also be added to Spark jobs launched through spark-shell or spark-submit by using the --packages command line option. For example, to include it when starting the spark shell:

$ bin/spark-shell --packages org.apache.bahir:spark-sql-streaming-sqs_{{site.SCALA_BINARY_VERSION}}:{{site.SPARK_VERSION}}

Unlike using --jars, using --packages ensures that this library and its dependencies will be added to the classpath. The --packages argument can also be used with bin/spark-submit.

This library is compiled for Scala 2.12 only, and intends to support Spark 2.4.0 onwards.

Configuration options

The configuration is obtained from parameters.

Name	Default	Meaning
sqsUrl	required, no default value	sqs queue url, like ‘https://sqs.us-east-1.amazonaws.com/330183209093/TestQueue’
region	required, no default value	AWS region where queue is created
fileFormat	required, no default value	file format for the s3 files stored on Amazon S3
schema	required, no default value	schema of the data being read
sqsFetchIntervalSeconds	10	time interval (in seconds) after which to fetch messages from Amazon SQS queue
sqsLongPollingWaitTimeSeconds	20	wait time (in seconds) for long polling on Amazon SQS queue
sqsMaxConnections	1	number of parallel threads to connect to Amazon SQS queue
sqsMaxRetries	10	Maximum number of consecutive retries in case of a connection failure to SQS before giving up
ignoreFileDeletion	false	whether to ignore any File deleted message in SQS queue
fileNameOnly	false	Whether to check new files based on only the filename instead of on the full path
shouldSortFiles	true	whether to sort files based on timestamp while listing them from SQS
useInstanceProfileCredentials	false	Whether to use EC2 instance profile credentials for connecting to Amazon SQS
maxFilesPerTrigger	no default value	maximum number of files to process in a microbatch
maxFileAge	7d	Maximum age of a file that can be found in this directory
messageWrapper	None	- ‘None’ if SQS contains plain S3 message. - ‘SNS’ if SQS contains S3 notification message which came from SNS. Please see ‘Use multiple consumers’ section for more details

Use multiple consumers

SQS cannot be read by multiple consumers.
If S3 path should be listen by multiple applications the following approach is recommended: S3 -> SNS -> SQS:

Create multiple SQS queues. Each application listen for one SQS queue.
Create 1 SNS topic
Once S3 notification event is pushed to SNS topic it will be delivered to each SQS queue

Thus, one S3 path can be processed by multiple applications.

Example

An example to create a SQL stream which uses Amazon SQS to list files on S3,

    val inputDf = sparkSession
                      .readStream
                      .format("s3-sqs")
                      .schema(schema)
                      .option("sqsUrl", queueUrl)
                      .option("fileFormat", "json")
                      .option("sqsFetchIntervalSeconds", "2")
                      .option("sqsLongPollingWaitTimeSeconds", "5")
                      .option("useInstanceProfileCredentials", "true")
                      .load()