val records = spark.
readStream
format("text").
load("server-logs/*.out").
as[String]
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) = {}
}
records.writeStream
.queryName("server-logs processor")
.foreach(writer)
.startForeachSink
ForeachSink is a typed streaming sink that passes rows (of the type T) to ForeachWriter (one record at a time per partition).
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Note
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ForeachSink is assigned a ForeachWriter when DataStreamWriter is started.
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ForeachSink is used exclusively in foreach operator.
Internally, addBatch (the only method from the Sink Contract) 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.
addBatch(batchId: Long, data: DataFrame): UnitaddBatch then opens the constructor’s ForeachWriter (for the current partition and the input batch) and passes the records to process (one at a time per partition).
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Caution
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FIXME Why does Spark track whether the writer failed or not? Why couldn’t it finally and do close?
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Caution
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FIXME Can we have a constant for "foreach" for source in DataStreamWriter?
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