Has anyone been able to run the code in The Future of Real-Time in Spark <http://rxin.github.io/talks/2016-02-18_spark_summit_streaming.pdf> Slide 24 :"Continuous Aggregation"?
Specifically, the line: stream("jdbc:mysql//..."), Using Spark 2.0 preview build, I am getting the error when writing to MySQL: Exception in thread "main" java.lang.UnsupportedOperationException: Data source jdbc does not support streamed writing at org.apache.spark.sql.execution.datasources.DataSource.createSink(DataSource.scala:201) My code: val logsDF = sparkSession.read.format("json") .stream("file:///xxx/xxx/spark-2.0.0-preview-bin-hadoop2.4/examples/src/main/resources/people.json") val logsDS = logsDF.as[Person] logsDS.groupBy("name").sum("age").write.format("jdbc").option("checkpointLocation", "/xxx/xxx/temp").startStream("jdbc:mysql//localhost/test") } Looking at the Spark DataSource.scala source code, looks like only ParquetFileFormat is supported? Am I missing something? What data sources support streamed write? Is the example code referring to 2.0 features? Thanks in advanced for your help. Chang -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Running-of-Continuous-Aggregation-example-tp27229.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org