[SPARK-27564] 'No plan for EventTimeWatermark' error while using structured streaming with column pruning

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Incomplete
• Affects Version/s: 2.3.1
• Component/s: Structured Streaming
• Labels: bulk-closed
• Assignee: Unassigned
• Reporter: Kineret
• Created: 25/Apr/19 08:56
• Updated: 25/May/21 01:55
• Resolved: 25/May/21 01:41

Description

I get 'No plan for EventTimeWatermark' error while doing a query with columns pruning using structured streaming with a custom data source that implements Spark datasource v2.

My data source implementation that handles the schemas includes the following: 

class MyDataSourceReader extends DataSourceReader with  SupportsPushDownRequiredColumns { 
    var schema: StructType = createSchema()

    override def readSchema(): StructType = schema

    override def pruneColumns(requiredSchema: StructType) = {
        this.schema = requiredSchema
    }

and then:

class MyDataSourceReaderStream extends MyDataSourceReader { ... }

This is my test code:

def x(): Unit = {
        val df1 = sparkSession.readStream.format(myV2Source).load()

        val df2 = df1
                .withColumn("epoch", (round(col("epoch")/(30*1000))*30).cast(TimestampType))
                .withWatermark("epoch", "1 milliseconds")
                .groupBy(col("epoch"), col("id")).count()

        val streamingQuery = df2
                .writeStream
                .format("console")
                .trigger(Trigger.ProcessingTime("10 seconds"))
                .outputMode(OutputMode.Append())
                .start()

        streamingQuery.awaitTermination()
   }

I get the following exception:

Caused by: java.lang.AssertionError: assertion failed: No plan for EventTimeWatermark epoch#201: timestamp, interval 1 milliseconds
+- Project [cast((round((cast(epoch#320L as double) / 30000.0), 0) * 30.0) as timestamp) AS epoch#201, id#367L]
   +- DataSourceV2Relation [epoch#320L, id#367L], com.akamai.csi.datacatalog.spark.connectors.endor.v2.reader.stream.EndorDataSourceStreamReader@173b1b7c

at scala.Predef$.assert(Predef.scala:170)
at org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:93)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2$$anonfun$apply$2.apply(QueryPlanner.scala:78)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2$$anonfun$apply$2.apply(QueryPlanner.scala:75)
at scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157)
at scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)

Note that in the logical plan I got DataSourceV2Relation and not StreamingDataSourceV2Relation although I use streaming.

Where is the problem?