nsivabalan commented on issue #5565:
URL: https://github.com/apache/hudi/issues/5565#issuecomment-1125513315
here is the forEachBatch that I have come across from some other community
user
```
val query = df.
writeStream.
queryName("demo").
foreachBatch { (batchDF: org.apache.spark.sql.DataFrame, _: Long) => {
batchDF.persist()
println(LocalDateTime.now() + " start writing cow table")
batchDF.write.format("org.apache.hudi").
option(TABLE_TYPE.key, "COPY_ON_WRITE").
option(PRECOMBINE_FIELD.key, "kafka_timestamp").
option(RECORDKEY_FIELD.key, "kafka_partition_offset").
option(PARTITIONPATH_FIELD.key, "partition_date").
option(HIVE_SYNC_ENABLED.key, false).
option(HIVE_STYLE_PARTITIONING.key, true).
option(FAIL_ON_TIMELINE_ARCHIVING_ENABLE.key, false).
option(STREAMING_IGNORE_FAILED_BATCH.key, false).
option(STREAMING_RETRY_CNT.key, 0).
option("hoodie.table.name", "copy_on_write_table").
option("hoodie.clustering.plan.strategy.target.file.max.bytes","10485760").
option("hoodie.clustering.plan.strategy.small.file.limit","50000").
option("hoodie.clustering.plan.strategy.sort.columns","partition_date,kafka_partition_offset").
option("hoodie.clustering.async.max.commits","2").
option("hoodie.datasource.clustering.async.enable","true").
option("hoodie.clustering.async.enabled","true").
option("hoodie.clustering.updates.strategy","org.apache.hudi.client.clustering.update.strategy.SparkAllowUpdateStrategy").
mode(Append).
save("/tmp/hudi_streaming_kafka/COPY_ON_WRITE")
println(LocalDateTime.now() + " finish")
batchDF.unpersist()
}
}.option("checkpointLocation",
"/tmp/hudi_streaming_kafka/checkpoint/").start()
```
this uses spark-datasource writes and not using streaming sink to write to
hudi.
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