Spark structured streaming JDBC source

• Overview:

A library for querying JDBC data with Apache Spark Structured Streaming, for Spark SQL and DataFrames.

• Build from Source

sbt "set test in assembly := {}" clean assembly

• Quick Example

import org.apache.spark.sql.functions._
import org.apache.spark.sql.SparkSession

val spark = SparkSession
  .builder
  .appName("StructuredJDBC")
  .getOrCreate()
  
import spark.implicits._

val jdbcOptions = Map(
    "user" -> "user",
    "password" -> "password",
    "database" -> "db name",
    "driver" -> "org.h2.Driver",
    "url" -> "jdbc:h2:mem:myDb;DB_CLOSE_DELAY=-1;DATABASE_TO_UPPER=false"
  )

// Create DataFrame representing the stream of input lines from jdbc
val stream = spark.readStream
      .format("jdbc-streaming")
      .options(jdbcOptions + ("dbtable" -> "source") + ("offsetColumn" -> "offsetColumn"))
      .load

// Start running the query that prints 'select result' to the console
val query = stream.writeStream
  .outputMode("append")
  .format("console")
  .start()

query.awaitTermination()

• Features

All JDBC connection parameters are set as in non-streaming reading (https://spark.apache.org/docs/latest/sql-data-sources-jdbc.html), except for the following:

offsetColumn : Required field, name of the column by which changes will be tracked. The following column types are supported:

• IntegerType
• LongType
• TimestampType
• DataType

startingoffset : The start point when a query is started, either "earliest" (default value) which is from the min offsetColumn value, "latest" which is just from the max offsetColumn value, or a string specifying a starting offset:

• IntegerType or LongType "0"
• TimestampType "2019-01-30 00:10:00"
• DataType "2019-03-20""

ToDo:

• Validate input options.
• make 'maxoffsetspertrigger' property.