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https://issues.apache.org/jira/browse/HBASE-20748?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16515872#comment-16515872
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Charles PORROT commented on HBASE-20748:
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PR has already been linked in the ticket (PR #78).
I will put the issue in "Patch Available."
Thank you for your time. I will try to follow the guidelines better if I have
another contribution to make.
> HBaseContext bulkLoad: being able to use custom versions
> --------------------------------------------------------
>
> Key: HBASE-20748
> URL: https://issues.apache.org/jira/browse/HBASE-20748
> Project: HBase
> Issue Type: Improvement
> Components: spark
> Reporter: Charles PORROT
> Assignee: Charles PORROT
> Priority: Major
> Labels: HBaseContext, bulkload, spark, versions
> Attachments: bulkLoadCustomVersions.scala
>
>
> The _bulkLoad_ methods of _class org.apache.hadoop.hbase.spark.HBaseContext_
> use the system's current time for the version of the cells to bulk-load. This
> makes this method, and its twin _bulkLoadThinRows_, useless if you need to
> use your own versionning system:
> {code:java}
> //Here is where we finally iterate through the data in this partition of the
> //RDD that has been sorted and partitioned
> val wl = writeValueToHFile(
> keyFamilyQualifier.rowKey,
> keyFamilyQualifier.family,
> keyFamilyQualifier.qualifier,
> cellValue,
> nowTimeStamp,
> fs,
> conn,
> localTableName,
> conf,
> familyHFileWriteOptionsMapInternal,
> hfileCompression,
> writerMap,
> stagingDir
> ){code}
>
> Thus, I propose a third _bulkLoad_ method, based on the original method.
> Instead of using an _Iterator(KeyFamilyQualifier, Array[Byte])_ as the basis
> for the writes, this new method would use an _Iterator(KeyFamilyQualifier,
> Array[Byte], Long_), with the _Long_ being the version.
>
> Definition of _bulkLoad_:
> {code:java}
> def bulkLoad[T](
> rdd:RDD[T],
> tableName: TableName,
> flatMap: (T) => Iterator[(KeyFamilyQualifier, Array[Byte])],
> stagingDir:String,
> familyHFileWriteOptionsMap: util.Map[Array[Byte], FamilyHFileWriteOptions] =
> new util.HashMap[Array[Byte], FamilyHFileWriteOptions],
> compactionExclude: Boolean = false,
> maxSize:Long = HConstants.DEFAULT_MAX_FILE_SIZE):{code}
> Definition of a _bulkLoadWithCustomVersions_ method:
> {code:java}
> def bulkLoadCustomVersions[T](rdd:RDD[T],
> tableName: TableName,
> flatMap: (T) => Iterator[(KeyFamilyQualifier, Array[Byte],
> Long)],
> stagingDir:String,
> familyHFileWriteOptionsMap:
> util.Map[Array[Byte], FamilyHFileWriteOptions] =
> new util.HashMap[Array[Byte], FamilyHFileWriteOptions],
> compactionExclude: Boolean = false,
> maxSize:Long = HConstants.DEFAULT_MAX_FILE_SIZE):{code}
> In case of illogical version (for instance, a negative version), the method
> would throw back to the current timestamp.
> {code:java}
> val wl = writeValueToHFile(keyFamilyQualifier.rowKey,
> keyFamilyQualifier.family,
> keyFamilyQualifier.qualifier,
> cellValue,
> if (version > 0) version else nowTimeStamp,
> fs,
> conn,
> localTableName,
> conf,
> familyHFileWriteOptionsMapInternal,
> hfileCompression,
> writerMap,
> stagingDir){code}
> See the attached file for the file with the full proposed method.
>
> +Edit:+
> The same could be done with bulkLoadThinRows: instead of a:
> {code:java}
> Iterator[Pair[ByteArrayWrapper, FamiliesQualifiersValues]]{code}
> We expect an:
> {code:java}
> Iterator[Triple[ByteArrayWrapper, FamiliesQualifiersValues, Long]]{code}
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