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https://issues.apache.org/jira/browse/HUDI-3242?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17479685#comment-17479685
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Harsha Teja Kanna commented on HUDI-3242:
-----------------------------------------
Let me try that.
Yes, I am aware that checkpoint need not be set for initial creation, It was
just my automation passing it by mistake found out the issue.
Also few of my unloaded datasets have non linear timestamps across partitions
and I create the hudi table partition after partition and set checkpoint to 0.
> Checkpoint 0 is ignored -Partial parquet file discovery after the first commit
> ------------------------------------------------------------------------------
>
> Key: HUDI-3242
> URL: https://issues.apache.org/jira/browse/HUDI-3242
> Project: Apache Hudi
> Issue Type: Bug
> Components: spark, writer-core
> Affects Versions: 0.10.1
> Environment: AWS
> EMR 6.4.0
> Spark 3.1.2
> Hudi - 0.10.1-rc
> Reporter: Harsha Teja Kanna
> Assignee: sivabalan narayanan
> Priority: Critical
> Labels: hudi-on-call, sev:critical, user-support-issues
> Attachments: Screen Shot 2022-01-13 at 2.40.55 AM.png, Screen Shot
> 2022-01-13 at 2.55.35 AM.png, Screen Shot 2022-01-20 at 1.36.48 PM.png
>
> Original Estimate: 3h
> Remaining Estimate: 3h
>
> Hi, I am testing release branch 0.10.1 as I needed few bug fixes from it.
> However, I see for a certain table. Only partial discovery of files happening
> after the initial commit of the table.
> But if the second partition is given as input for the first commit, all the
> files are getting discovered.
> First partition : 2021/01 has 744 files and all of them are discovered
> Second partition: 2021/02 has 762 files but only 72 are discovered.
> Checkpoint is set to 0.
> No errors in the logs.
> {code:java}
> spark-submit \
> --master yarn \
> --deploy-mode cluster \
> --driver-cores 30 \
> --driver-memory 32g \
> --executor-cores 5 \
> --executor-memory 32g \
> --num-executors 120 \
> --jars
> s3://bucket/apps/datalake/jars/unused-1.0.0.jar,s3://bucket/apps/datalake/jars/spark-avro_2.12-3.1.2.jar
> \
> --class org.apache.hudi.utilities.deltastreamer.HoodieDeltaStreamer \
> --conf spark.serializer=org.apache.spark.serializer.KryoSerializer
> s3://bucket/apps/datalake/jars/hudi-0.10.0/hudi-utilities-bundle_2.12-0.10.0.jar
> \
> --table-type COPY_ON_WRITE \
> --source-ordering-field timestamp \
> --source-class org.apache.hudi.utilities.sources.ParquetDFSSource \
> --target-base-path s3a://datalake-hudi/datastream/v1/sessions_by_date \
> --target-table sessions_by_date \
> --transformer-class
> org.apache.hudi.utilities.transform.SqlQueryBasedTransformer \
> --op INSERT \
> --checkpoint 0 \
> --hoodie-conf hoodie.clean.automatic=true \
> --hoodie-conf hoodie.cleaner.commits.retained=1 \
> --hoodie-conf hoodie.cleaner.policy=KEEP_LATEST_COMMITS \
> --hoodie-conf hoodie.clustering.inline=false \
> --hoodie-conf hoodie.clustering.inline.max.commits=1 \
> --hoodie-conf
> hoodie.clustering.plan.strategy.class=org.apache.hudi.client.clustering.plan.strategy.SparkSizeBasedClusteringPlanStrategy
> \
> --hoodie-conf hoodie.clustering.plan.strategy.max.num.groups=1000000 \
> --hoodie-conf hoodie.clustering.plan.strategy.small.file.limit=250000000 \
> --hoodie-conf hoodie.clustering.plan.strategy.sort.columns=sid,id \
> --hoodie-conf hoodie.clustering.plan.strategy.target.file.max.bytes=268435456
> \
> --hoodie-conf hoodie.clustering.preserve.commit.metadata=true \
> --hoodie-conf hoodie.datasource.hive_sync.database=datalake-hudi \
> --hoodie-conf hoodie.datasource.hive_sync.enable=false \
> --hoodie-conf hoodie.datasource.hive_sync.ignore_exceptions=true \
> --hoodie-conf hoodie.datasource.hive_sync.mode=hms \
> --hoodie-conf
> hoodie.datasource.hive_sync.partition_extractor_class=org.apache.hudi.hive.HiveStylePartitionValueExtractor
> \
> --hoodie-conf hoodie.datasource.hive_sync.table=sessions_by_date \
> --hoodie-conf hoodie.datasource.hive_sync.use_jdbc=false \
> --hoodie-conf hoodie.datasource.write.hive_style_partitioning=true \
> --hoodie-conf
> hoodie.datasource.write.keygenerator.class=org.apache.hudi.keygen.CustomKeyGenerator
> \
> --hoodie-conf hoodie.datasource.write.operation=insert \
> --hoodie-conf hoodie.datasource.write.partitionpath.field=date:TIMESTAMP \
> --hoodie-conf hoodie.datasource.write.precombine.field=timestamp \
> --hoodie-conf hoodie.datasource.write.recordkey.field=id,qid,aid \
> --hoodie-conf
> hoodie.deltastreamer.keygen.timebased.input.dateformat=yyyy/MM/dd \
> --hoodie-conf hoodie.deltastreamer.keygen.timebased.input.timezone=GMT \
> --hoodie-conf
> hoodie.deltastreamer.keygen.timebased.output.dateformat=yyyy/MM/dd \
> --hoodie-conf hoodie.deltastreamer.keygen.timebased.output.timezone=GMT \
> --hoodie-conf
> hoodie.deltastreamer.keygen.timebased.timestamp.type=DATE_STRING \
> --hoodie-conf
> hoodie.deltastreamer.source.dfs.root=s3://datalake-hudi/history/datastream/v1/sessions/2021/02
> \
> --hoodie-conf
> hoodie.deltastreamer.source.input.selector=org.apache.hudi.utilities.sources.helpers.DFSPathSelector
> \
> --hoodie-conf "\"hoodie.deltastreamer.transformer.sql=SELECT id, qid, aid,
> to_timestamp(timestamp) as timestamp, sid,
> date_format(to_timestamp(timestamp), 'yyyy/MM/dd') AS date FROM <SRC> a \"" \
> --hoodie-conf hoodie.file.listing.parallelism=256 \
> --hoodie-conf hoodie.finalize.write.parallelism=256 \
> --hoodie-conf
> hoodie.generate.consistent.timestamp.logical.for.key.generator=true \
> --hoodie-conf hoodie.insert.shuffle.parallelism=1000 \
> --hoodie-conf hoodie.metadata.enable=true \
> --hoodie-conf hoodie.metadata.metrics.enable=true \
> --hoodie-conf
> hoodie.metrics.cloudwatch.metric.prefix=emr.datalake-service.prd.insert.sessions_by_date
> \
> --hoodie-conf hoodie.metrics.on=true \
> --hoodie-conf hoodie.metrics.reporter.type=CLOUDWATCH \
> --hoodie-conf hoodie.parquet.block.size=268435456 \
> --hoodie-conf hoodie.parquet.compression.codec=snappy \
> --hoodie-conf hoodie.parquet.max.file.size=268435456 \
> --hoodie-conf hoodie.parquet.small.file.limit=250000000 {code}
>
>
>
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