Slow Write into Hudi Dataset(MOR)

Hi Team,

I am reading data from Kafka and ingesting data into Hudi Dataset(MOR) using Hudi DataSource Api through Spark Structured Streaming. Pipeline Structure as like -

Kafka(Source) > Spark Structured Streaming(EMR) > MOR Hudi table(S3)

Spark - 2.4.5 Hudi - 0.5.2

I am getting performance issues while writing data into Hudi Dataset. following Hudi Jobs are taking time countByKey at HoodieBloomIndex.java countByKey at WorkloadProfile.java count at HoodieSparkSqlWriter.scala

Configuration used to write hudi data set as followed

new_df.write.format("org.apache.hudi").option("hoodie.table.name", tableName) \
    .option("hoodie.datasource.write.operation", "upsert") \
    .option("hoodie.datasource.write.table.type", "MERGE_ON_READ") \
    .option("hoodie.datasource.write.recordkey.field", "wbn") \
    .option("hoodie.datasource.write.partitionpath.field", "ad") \
    .option("hoodie.datasource.write.precombine.field", "action_date") \
    .option("hoodie.compact.inline", "true") \
    .option("hoodie.compact.inline.max.delta.commits", "300") \
    .option("hoodie.datasource.hive_sync.enable", "true") \
    .option("hoodie.upsert.shuffle.parallelism", "5") \
    .option("hoodie.insert.shuffle.parallelism", "5") \
    .option("hoodie.bulkinsert.shuffle.parallelism", "5") \
    .option("hoodie.datasource.hive_sync.table", tableName) \
    .option("hoodie.datasource.hive_sync.partition_fields", "ad") \
    .option("hoodie.index.type","GLOBAL_BLOOM") \
    .option("hoodie.bloom.index.update.partition.path", "true") \
    .option("hoodie.datasource.hive_sync.assume_date_partitioning", "false") \
    .option("hoodie.datasource.hive_sync.partition_extractor_class",
            "org.apache.hudi.hive.MultiPartKeysValueExtractor") \
    .mode("append").save(tablePath)

Spark Submit command - spark-submit --deploy-mode client --master yarn –executor-memory 6g --executor-cores 1 –driver-memory 4g –conf spark.driver.maxResultSize=2g –conf spark.executor.id=driver –conf spark.executor.instances=300 –conf spark.kryoserializer.buffer.max=512m –conf spark.shuffle.service.enabled=true –conf spark.sql.hive.convertMetastoreParquet=false –conf spark.task.cpus=1 –conf spark.yarn.driver.memoryOverhead=1024 –conf spark.yarn.executor.memoryOverhead=3072 –conf spark.yarn.max.executor.failures=100 –jars /usr/lib/hudi/hudi-spark-bundle.jar,/usr/lib/spark/external/lib/spark-avro.jar –packages org.apache.spark:spark-sql-kafka-0-10_2.11:2.4.4 –py-files s3://spark-test/hudi_job.py Attaching screen shot for the job details.

countByKey at HoodieBloomIndex.java

countByKey at WorkloadProfile.java

count at HoodieSparkSqlWriter.scala

Please suggest how I can tune this.

Thanks Raghvendra

[Raghvendradubey]

@vinothchandar I run the job with 5 min batch interval using MOR, now I can see commit duration are 5 min and compaction is also 5 min, and updated records are only 10% of total records written but now job is running with huge lag. sample commit are as below -

═══════════╗
║ CommitTime     │ Total Bytes Written │ Total Files Added │ Total Files Updated │ Total Partitions Written │ Total Records Written │ Total Update Records Written │ Total Errors ║
╠════════════════╪═════════════════════╪═══════════════════╪═════════════════════╪══════════════════════════╪═══════════════════════╪══════════════════════════════╪══════════════╣
║ 20200625112117 │ 178.0 MB            │ 1                 │ 3                   │ 2                        │ 193777                │ 18939                        │ 0            ║
╟────────────────┼─────────────────────┼───────────────────┼─────────────────────┼──────────────────────────┼───────────────────────┼──────────────────────────────┼──────────────╢
║ 20200625111810 │ 104.0 MB            │ 0                 │ 1                   │ 1                        │ 149946                │ 12619                        │ 0            ║
╟────────────────┼─────────────────────┼───────────────────┼─────────────────────┼──────────────────────────┼───────────────────────┼──────────────────────────────┼──────────────╢
║ 20200625111610 │ 211.7 MB            │ 0                 │ 3                   │ 2                        │ 259500                │ 14721                        │ 0            ║

[nsivabalan]

we have done lot of improvements around perf w/ hudi. https://hudi.apache.org/blog/2022/06/29/Apache-Hudi-vs-Delta-Lake-transparent-tpc-ds-lakehouse-performance-benchmarks

Can you try out 0.12. Also, we have written a blog around diff indexes in hudi and when to use what. https://hudi.apache.org/blog/2020/11/11/hudi-indexing-mechanisms/ Might benefit in your use-case.

Closing it out due to long inactivity. Feel free to re-open or open a new issue if you need assistance.