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ForeachSink is a typed streaming sink that passes rows (of the type T) to ForeachWriter (one record at a time per partition).


ForeachSink is assigned a ForeachWriter when DataStreamWriter is started.

ForeachSink is used exclusively in foreach operator.

val records = spark.

import org.apache.spark.sql.ForeachWriter
val writer = new ForeachWriter[String] {
  override def open(partitionId: Long, version: Long) = true
  override def process(value: String) = println(value)
  override def close(errorOrNull: Throwable) = {}

  .queryName("server-logs processor")

Internally, addBatch (the only method from the <>) takes records from the input[DataFrame] (as data), transforms them to expected type T (of this ForeachSink) and (now as a[Dataset])[processes each partition].

[source, scala]

addBatch(batchId: Long, data: DataFrame): Unit

addBatch then opens the constructor's datasources/foreach/[ForeachWriter] (for the[current partition] and the input batch) and passes the records to process (one at a time per partition).

CAUTION: FIXME Why does Spark track whether the writer failed or not? Why couldn't it finally and do close?

CAUTION: FIXME Can we have a constant for "foreach" for source in DataStreamWriter?