redsk commented on a change in pull request #26153: [SPARK-29500][SQL][SS]
Support partition column when writing to Kafka
URL: https://github.com/apache/spark/pull/26153#discussion_r336382437
##########
File path:
external/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaSinkSuite.scala
##########
@@ -404,20 +420,85 @@ abstract class KafkaSinkBatchSuiteBase extends
KafkaSinkSuiteBase {
.save()
checkAnswer(
createKafkaReader(topic, includeHeaders = true).selectExpr(
- "CAST(value as STRING) value", "headers"
+ "CAST(value as STRING) value", "headers", "partition"
),
- Row("1", Seq(Row("a", "b".getBytes(UTF_8)))) ::
- Row("2", Seq(Row("c", "d".getBytes(UTF_8)), Row("e",
"f".getBytes(UTF_8)))) ::
- Row("3", Seq(Row("g", "h".getBytes(UTF_8)), Row("g",
"i".getBytes(UTF_8)))) ::
- Row("4", null) ::
+ Row("1", Seq(Row("a", "b".getBytes(UTF_8))), 0) ::
+ Row("2", Seq(Row("c", "d".getBytes(UTF_8)), Row("e",
"f".getBytes(UTF_8))), 1) ::
+ Row("3", Seq(Row("g", "h".getBytes(UTF_8)), Row("g",
"i".getBytes(UTF_8))), 2) ::
+ Row("4", null, 3) ::
Row("5", Seq(
Row("j", "k".getBytes(UTF_8)),
Row("j", "l".getBytes(UTF_8)),
- Row("m", "n".getBytes(UTF_8)))) ::
+ Row("m", "n".getBytes(UTF_8))), 0) ::
Nil
)
}
+ test("batch - partition column vs default Kafka partitioner") {
+ val fixedKey = "fixed_key"
+ val nrPartitions = 100
+
+ // default Kafka partitioner calculate partition deterministically based
on the key
+ val keyTopic = newTopic()
+ testUtils.createTopic(keyTopic, nrPartitions)
+
+ Seq((keyTopic, fixedKey, "value"))
+ .toDF("topic", "key", "value")
+ .write
+ .format("kafka")
+ .option("kafka.bootstrap.servers", testUtils.brokerAddress)
+ .option("topic", keyTopic)
+ .mode("append")
+ .save()
+
+ // getting the partition corresponding to the fixed key
+ val keyPartition = createKafkaReader(keyTopic).select("partition")
+ .map(_.getInt(0)).collect().toList.head
+
+ val topic = newTopic()
+ testUtils.createTopic(topic, nrPartitions)
+
+ // even values use default kafka partitioner, odd use 'n'
+ val df = (0 until 100)
+ .map(n => (topic, fixedKey, s"$n", if (n % 2 == 0) None else Some(n)))
+ .toDF("topic", "key", "value", "partition")
+
+ df.write
+ .format("kafka")
+ .option("kafka.bootstrap.servers", testUtils.brokerAddress)
+ .option("topic", topic)
+ .mode("append")
+ .save()
+
+ checkAnswer(
+ createKafkaReader(topic).selectExpr(
+ "CAST(key as STRING) key", "CAST(value as STRING) value", "partition"
+ ),
+ (0 until 100)
+ .map(n => (fixedKey, s"$n", if (n % 2 == 0) keyPartition else n))
+ .toDF("key", "value", "partition")
+ )
+ }
+
+ test("batch - non-existing partitions trigger standard Kafka exception") {
Review comment:
My main question was: "what happens if I specify partitions that don't
exist?" And the answer is that Kafka throws an exception with msg: `Topic
$topic not present in metadata after $producerTimeout ms` which is not
particularly clear.
I could have called `producer.partitionsFor(topic)` to check if the
specified partition is in range (and throw a more meaningful exception if not)
but it's an expensive call for each message. I could cache the result but the
number of partitions could change in between calls and I didn't want to
complicate the implementation. Hence the need to see what the standard Kafka
producer does (which is "not much").
And the rationale is: if Kafka implementation changes, this test will fail
and we'll have a chance to provide a more meaningful exception.
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