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[GitHub] [hudi] pengzhiwei2018 opened a new pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
pengzhiwei2018 opened a new pull request #3328:
URL: https://github.com/apache/hudi/pull/3328
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[GitHub] [hudi] nsivabalan commented on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-894355629
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] nsivabalan commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r682137257
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
+ // insert overwrite table
+ case (_, _, true, _) if !isPartitionedTable => INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
+ // if the table has primaryKey and the dropDuplicate has disable, use the upsert operation
+ case (true, false, false, false) => UPSERT_OPERATION_OPT_VAL
+ // if enableBulkInsert is true and the table is non-primaryKeyed, use the bulk insert operation
+ case (false, true, _, _) => BULK_INSERT_OPERATION_OPT_VAL
+ // for the rest case, use the insert operation
+ case (_, _, _, _) => INSERT_OPERATION_OPT_VAL
Review comment:
actually I came across [INSERT OVERWRITE DIRECTORY](https://spark.apache.org/docs/latest/sql-ref-syntax-dml-insert-overwrite-directory.html) which can be mapped to insert_overwrite.
Here is a suggestion w/o using any additional configs:
CTAS -> bulk_insert
Insert into -> insert
INSERT OVERWRITE -> insert overwrite table
INSERT OVERWRITE DIRECTORY -> insert overwrite (partitions)
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[GitHub] [hudi] pengzhiwei2018 edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-894613109
Hi @nsivabalan , The PR has updated with the follow chanes:
add "upsert" mode for insert.mode. Currently we have 3 insert mode:
- upsert
In upsert mode for insert into, duplicate record on primary key will be updated.This is the default insert mode for pk-table.
- strict
In strict mode for insert into, we do the pk uniqueness guarantee for COW pk-table. For MOR pk-table, it has the same behavior with "upsert" mode.
- non-strict
In non-strict mode for insert into, we use insert operation to write data which allow writing the duplicate record.
The default insert mode is `upsert` for pk-table.
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[GitHub] [hudi] nsivabalan commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r682101452
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
+ // insert overwrite table
+ case (_, _, true, _) if !isPartitionedTable => INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
+ // if the table has primaryKey and the dropDuplicate has disable, use the upsert operation
+ case (true, false, false, false) => UPSERT_OPERATION_OPT_VAL
+ // if enableBulkInsert is true and the table is non-primaryKeyed, use the bulk insert operation
+ case (false, true, _, _) => BULK_INSERT_OPERATION_OPT_VAL
+ // for the rest case, use the insert operation
+ case (_, _, _, _) => INSERT_OPERATION_OPT_VAL
Review comment:
@vinothchandar : do check this out before reviewing other feedbacks.
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[GitHub] [hudi] nsivabalan commented on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-894571028
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] pengzhiwei2018 edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-894613109
Hi @nsivabalan , The PR has updated with the follow chanes:
add "upsert" mode for insert.mode. Currently we have 3 insert mode:
- upsert
In upsert mode for insert into, duplicate record on primary key will be updated.This is the default insert mode for pk-table.
- strict
In strict mode for insert into, we do the pk uniqueness guarantee for COW pk-table. For MOR pk-table, it has the same behavior with "upsert" mode.
- non-strict
In non-strict mode for insert into, we use insert operation to write data which allow writing the duplicate record.
The default insert mode is `upsert` for pk-table.
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[GitHub] [hudi] nsivabalan commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r684803078
##########
File path: hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/TestInsertTable.scala
##########
@@ -303,5 +304,184 @@ class TestInsertTable extends TestHoodieSqlBase {
"assertion failed: Required select columns count: 4, Current select columns(including static partition column)" +
" count: 3,columns: (1,a1,10)"
)
+ spark.sql("set hoodie.sql.bulk.insert.enable = true")
+ spark.sql("set hoodie.sql.insert.mode= strict")
+
+ val tableName2 = generateTableName
Review comment:
Can we also enhance the test w/ both type of partitions(single level and multi-level).
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[GitHub] [hudi] nsivabalan commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r682137257
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
+ // insert overwrite table
+ case (_, _, true, _) if !isPartitionedTable => INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
+ // if the table has primaryKey and the dropDuplicate has disable, use the upsert operation
+ case (true, false, false, false) => UPSERT_OPERATION_OPT_VAL
+ // if enableBulkInsert is true and the table is non-primaryKeyed, use the bulk insert operation
+ case (false, true, _, _) => BULK_INSERT_OPERATION_OPT_VAL
+ // for the rest case, use the insert operation
+ case (_, _, _, _) => INSERT_OPERATION_OPT_VAL
Review comment:
actually I came across [INSERT OVERWRITE DIRECTORY](https://spark.apache.org/docs/latest/sql-ref-syntax-dml-insert-overwrite-directory.html) which can be mapped to insert_overwrite.
Here is a suggestion w/o using any additional configs:
CTAS -> bulk_insert
Insert into -> insert
INSERT OVERWRITE -> insert overwrite table
INSERT OVERWRITE DIRECTORY -> insert overwrite
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[GitHub] [hudi] nsivabalan commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r679153080
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
Review comment:
also, if there are any valid optimizations, then probably we should move it to HoodiesparkSqlSwriter so that both spark datasource and sql dml benefits :)
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[GitHub] [hudi] nsivabalan commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r680212711
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
+ // insert overwrite table
+ case (_, _, true, _) if !isPartitionedTable => INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
+ // if the table has primaryKey and the dropDuplicate has disable, use the upsert operation
+ case (true, false, false, false) => UPSERT_OPERATION_OPT_VAL
+ // if enableBulkInsert is true and the table is non-primaryKeyed, use the bulk insert operation
+ case (false, true, _, _) => BULK_INSERT_OPERATION_OPT_VAL
+ // for the rest case, use the insert operation
+ case (_, _, _, _) => INSERT_OPERATION_OPT_VAL
Review comment:
Here is my thought on choosing the right operation. Having too many case statements might complicate things and is error prone too. As I mentioned earlier, we should try to do any valid conversions in HoodiesSparkSqlWriter. Only those thats applicable just to sql dml, we should keep it here.
Anyways, here is one simplified approach. Ignoring the primary, non primary key table for now. We can come back to that later once we have consensus on this.
We need just two configs.
hoodie.sql.enable.bulk_insert (default false)
hoodie.sql.overwrite.entire.table (default true)
From sql syntax, there are two commands allowed.
"INSERT" into and "INSERT OVERWRITE". And these need to map to 4 operations on the hudi end (insert, bulk_insert, insert over write and insert overwrite table)
"INSERT" with no other configs set -> insert operation
"INSERT" with enable bulk insert set -> bulk_insert
"INSERT OVERWRITE" with no other configs set -> insert_overwrite_table operation
"INSERT OVERWRITE" with hoodie.sql.overwrite.entire.table = false -> insert_overwrite operation.
"INSERT OVERWRITE" with enable bulk_insert set -> bulk_insert. pass the right save mode to HoodieSparkSqlWriter
"INSERT OVERWRITE" with enable bulk_insert set and hoodie.sql.overwrite.entire.table = false -> bulk_insert. pass the right save mode to HoodieSparkSqlWriter.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] leesf commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
leesf commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r674866640
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/HoodieSparkSqlWriter.scala
##########
@@ -159,7 +159,10 @@ object HoodieSparkSqlWriter {
// Convert to RDD[HoodieRecord]
val genericRecords: RDD[GenericRecord] = HoodieSparkUtils.createRdd(df, schema, structName, nameSpace)
- val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean || operation.equals(WriteOperationType.UPSERT);
+ val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean ||
+ operation.equals(WriteOperationType.UPSERT) ||
+ parameters.getOrElse(HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key(),
Review comment:
here is a bug?
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
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[GitHub] [hudi] pengzhiwei2018 commented on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-886327353
Hi @leesf , I have introduced another config key to enable the bulk insert for sql. Please take a review when you have time~
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
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[GitHub] [hudi] pengzhiwei2018 commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r680693753
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -243,6 +256,8 @@ object InsertIntoHoodieTableCommand {
RECORDKEY_FIELD_OPT_KEY.key -> primaryColumns.mkString(","),
PARTITIONPATH_FIELD_OPT_KEY.key -> partitionFields,
PAYLOAD_CLASS_OPT_KEY.key -> payloadClassName,
+ ENABLE_ROW_WRITER_OPT_KEY.key -> enableBulkInsert.toString,
+ HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key -> isPrimaryKeyTable.toString, // if the table has primaryKey, enable the combine
Review comment:
Just like the upsert operation, Hudi do the combine automatic, we can do this for the user too which is much friendly for our users.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] nsivabalan commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r677405475
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
Review comment:
may I know why do we have this constraint?
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/HoodieSparkSqlWriter.scala
##########
@@ -159,7 +159,10 @@ object HoodieSparkSqlWriter {
// Convert to RDD[HoodieRecord]
val genericRecords: RDD[GenericRecord] = HoodieSparkUtils.createRdd(df, schema, structName, nameSpace)
- val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean || operation.equals(WriteOperationType.UPSERT);
+ val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean ||
+ operation.equals(WriteOperationType.UPSERT) ||
+ parameters.getOrElse(HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key(),
Review comment:
sorry I don't get you. Precombine is just one field as is right. Not sure what do you mean by "not compute the preCombine field value"? can you throw some more light please.
In general, for inserts we don't do any precombine. But if this config (COMBINE_BEFORE_INSERT_PROP) is enabled, we need to do preCombine.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -243,6 +256,8 @@ object InsertIntoHoodieTableCommand {
RECORDKEY_FIELD_OPT_KEY.key -> primaryColumns.mkString(","),
PARTITIONPATH_FIELD_OPT_KEY.key -> partitionFields,
PAYLOAD_CLASS_OPT_KEY.key -> payloadClassName,
+ ENABLE_ROW_WRITER_OPT_KEY.key -> enableBulkInsert.toString,
Review comment:
you can add one, but make the default as true.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
Review comment:
Am just trying to understand the sql dml here. We already handle save modes within HoodieSparkSqlWriter. So, trying to understand whats required in addition to that? Trying to avoid duplication if possible. I mean, for some of the cases listed here, its just about overWrite mode.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/HoodieSparkSqlWriter.scala
##########
@@ -159,7 +159,10 @@ object HoodieSparkSqlWriter {
// Convert to RDD[HoodieRecord]
val genericRecords: RDD[GenericRecord] = HoodieSparkUtils.createRdd(df, schema, structName, nameSpace)
- val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean || operation.equals(WriteOperationType.UPSERT);
+ val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean ||
+ operation.equals(WriteOperationType.UPSERT) ||
+ parameters.getOrElse(HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key(),
Review comment:
also, if its something that required just for sql dml, then we should probably think about adding it to sql dml classes and not here which spans spark datasource as well.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] leesf commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
leesf commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r676542368
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -243,6 +256,8 @@ object InsertIntoHoodieTableCommand {
RECORDKEY_FIELD_OPT_KEY.key -> primaryColumns.mkString(","),
PARTITIONPATH_FIELD_OPT_KEY.key -> partitionFields,
PAYLOAD_CLASS_OPT_KEY.key -> payloadClassName,
+ ENABLE_ROW_WRITER_OPT_KEY.key -> enableBulkInsert.toString,
Review comment:
here enableBulkInsert means using ROW_WRITER, should we also introduce another config to control the ROW_WRITER?
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[GitHub] [hudi] nsivabalan merged pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan merged pull request #3328:
URL: https://github.com/apache/hudi/pull/3328
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[GitHub] [hudi] pengzhiwei2018 commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r675960618
##########
File path: hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/TestInsertTable.scala
##########
@@ -144,7 +145,7 @@ class TestInsertTable extends TestHoodieSqlBase {
| partitioned by (dt)
| location '${tmp.getCanonicalPath}/$tableName'
""".stripMargin)
-
+ spark.sql("set hoodie.datasource.write.row.writer.enable = false")
Review comment:
remove this now
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[GitHub] [hudi] pengzhiwei2018 commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r676621769
##########
File path: hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/DataSourceOptions.scala
##########
@@ -247,6 +247,13 @@ object DataSourceWriteOptions {
.defaultValue("false")
.withDocumentation("When set to true, will perform write operations directly using the spark native " +
"`Row` representation, avoiding any additional conversion costs.")
+ /**
+ * Enable the bulk insert for sql insert statement.
+ */
+ val SQL_ENABLE_BULK_INSERT:ConfigProperty[String] = ConfigProperty
+ .key("hoodie.sq.bulk.insert.enable")
Review comment:
Good catch!
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -243,6 +256,8 @@ object InsertIntoHoodieTableCommand {
RECORDKEY_FIELD_OPT_KEY.key -> primaryColumns.mkString(","),
PARTITIONPATH_FIELD_OPT_KEY.key -> partitionFields,
PAYLOAD_CLASS_OPT_KEY.key -> payloadClassName,
+ ENABLE_ROW_WRITER_OPT_KEY.key -> enableBulkInsert.toString,
Review comment:
Currently we already have the ENABLE_ROW_WRITER_OPT_KEY to config the Row write. The enableBulkInsert is only used to control the row write for bulk insert.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -243,6 +256,8 @@ object InsertIntoHoodieTableCommand {
RECORDKEY_FIELD_OPT_KEY.key -> primaryColumns.mkString(","),
PARTITIONPATH_FIELD_OPT_KEY.key -> partitionFields,
PAYLOAD_CLASS_OPT_KEY.key -> payloadClassName,
+ ENABLE_ROW_WRITER_OPT_KEY.key -> enableBulkInsert.toString,
+ HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key -> isPrimaryKeyTable.toString, // if the table has primaryKey, enable the combine
Review comment:
Because we must guarantee the uniqueness for p-k table. So we should combine the input for pk-table.
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[GitHub] [hudi] pengzhiwei2018 commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r683207185
##########
File path: hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/DataSourceOptions.scala
##########
@@ -248,6 +248,14 @@ object DataSourceWriteOptions {
.withDocumentation("When set to true, will perform write operations directly using the spark native " +
"`Row` representation, avoiding any additional conversion costs.")
+ /**
+ * Enable the bulk insert for sql insert statement.
+ */
+ val SQL_ENABLE_BULK_INSERT:ConfigProperty[String] = ConfigProperty
Review comment:
Sound reasonable about this. CTAS use the bulk_insert by default, and regular insert for insert into by default.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
Review comment:
For CTAS, we can relax this. Because there is no data exist in the target table. We can just combine the input by pk before bulk insert to reach the same goal.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/HoodieSparkSqlWriter.scala
##########
@@ -159,7 +159,10 @@ object HoodieSparkSqlWriter {
// Convert to RDD[HoodieRecord]
val genericRecords: RDD[GenericRecord] = HoodieSparkUtils.createRdd(df, schema, structName, nameSpace)
- val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean || operation.equals(WriteOperationType.UPSERT);
+ val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean ||
+ operation.equals(WriteOperationType.UPSERT) ||
+ parameters.getOrElse(HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key(),
Review comment:
@vinothchandar well I think INSERT_DROP_DUPS_OPT_KEY is some different from COMBINE_BEFORE_INSERT_PROP.
**INSERT_DROP_DUPS_OPT_KEY**: is used to drop the duplicate record in the target table.
`COMBINE_BEFORE_INSERT_PROP`: is used to combine the duplicate record in the input.
So they are not total the same config. IMO.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
Review comment:
Well, in spark-sql , `insert overwrite partitioned table ` do not has the meaning of insert overwrite all the table. It is only overwrite the affected partitions.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
Review comment:
Yes, currently bulk insert has not support INSERT_OVERWRITE operation. So we cannot convert the` insert overwrite partitioned table ` statement to bulk insert.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
+ // insert overwrite table
+ case (_, _, true, _) if !isPartitionedTable => INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
Review comment:
Yes, but is cannot convert the write operation type for sql's insert statement. Here we must do the convert and pass the write type to HoodieSparkSqlWriter.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
Review comment:
Yes, the validate is some duplication here. But to keep the logic intact, I think we should keep this.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
+ // insert overwrite table
+ case (_, _, true, _) if !isPartitionedTable => INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
+ // if the table has primaryKey and the dropDuplicate has disable, use the upsert operation
+ case (true, false, false, false) => UPSERT_OPERATION_OPT_VAL
Review comment:
As we said above, we need do the pk uniqueness check. So we need use the upsert to reach this goal by a custom Playload class.
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[GitHub] [hudi] pengzhiwei2018 commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r683207185
##########
File path: hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/DataSourceOptions.scala
##########
@@ -248,6 +248,14 @@ object DataSourceWriteOptions {
.withDocumentation("When set to true, will perform write operations directly using the spark native " +
"`Row` representation, avoiding any additional conversion costs.")
+ /**
+ * Enable the bulk insert for sql insert statement.
+ */
+ val SQL_ENABLE_BULK_INSERT:ConfigProperty[String] = ConfigProperty
Review comment:
Sound reasonable about this. CTAS use the bulk_insert by default, and regular insert for insert into by default.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
Review comment:
For CTAS, we can relax this. Because there is no data exist in the target table. We can just combine the input by pk before bulk insert to reach the same goal.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/HoodieSparkSqlWriter.scala
##########
@@ -159,7 +159,10 @@ object HoodieSparkSqlWriter {
// Convert to RDD[HoodieRecord]
val genericRecords: RDD[GenericRecord] = HoodieSparkUtils.createRdd(df, schema, structName, nameSpace)
- val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean || operation.equals(WriteOperationType.UPSERT);
+ val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean ||
+ operation.equals(WriteOperationType.UPSERT) ||
+ parameters.getOrElse(HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key(),
Review comment:
@vinothchandar well I think INSERT_DROP_DUPS_OPT_KEY is some different from COMBINE_BEFORE_INSERT_PROP.
**INSERT_DROP_DUPS_OPT_KEY**: is used to drop the duplicate record in the target table.
`COMBINE_BEFORE_INSERT_PROP`: is used to combine the duplicate record in the input.
So they are not total the same config. IMO.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
Review comment:
Well, in spark-sql , `insert overwrite partitioned table ` do not has the meaning of insert overwrite all the table. It is only overwrite the affected partitions.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
Review comment:
Yes, currently bulk insert has not support INSERT_OVERWRITE operation. So we cannot convert the` insert overwrite partitioned table ` statement to bulk insert.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
+ // insert overwrite table
+ case (_, _, true, _) if !isPartitionedTable => INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
Review comment:
Yes, but is cannot convert the write operation type for sql's insert statement. Here we must do the convert and pass the write type to HoodieSparkSqlWriter.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
Review comment:
Yes, the validate is some duplication here. But to keep the logic intact, I think we should keep this.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
+ // insert overwrite table
+ case (_, _, true, _) if !isPartitionedTable => INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
+ // if the table has primaryKey and the dropDuplicate has disable, use the upsert operation
+ case (true, false, false, false) => UPSERT_OPERATION_OPT_VAL
Review comment:
As we said above, we need do the pk uniqueness check. So we need use the upsert to reach this goal by a custom Playload class.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] pengzhiwei2018 commented on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-893396472
@vinothchandar @nsivabalan The PR has updated with the follow changes:
1、Allow bulk insert for pk-table.
I introduce a config: `hoodie.sql.insert.mode` . If set to "strict", we will do the pk uniqueness guarantee. If set to "non-strict", we will ignore the uniqueness guarantee for pk table. The bulk insert is support in the case. By default the value is "non-strict".
2、CTAS use bulk insert by default.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] nsivabalan commented on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-894939778
thanks for your contribution! Good job 👍
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[GitHub] [hudi] pengzhiwei2018 commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r679789141
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
Review comment:
HoodieSparkSqlWriter cannot handle the mode for` insert overwrite partitioned table`, we should translate the write type to INSERT_OVERWRITE_TABLE for such case.
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[GitHub] [hudi] pengzhiwei2018 commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r684870787
##########
File path: hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/TestInsertTable.scala
##########
@@ -303,5 +304,184 @@ class TestInsertTable extends TestHoodieSqlBase {
"assertion failed: Required select columns count: 4, Current select columns(including static partition column)" +
" count: 3,columns: (1,a1,10)"
)
+ spark.sql("set hoodie.sql.bulk.insert.enable = true")
+ spark.sql("set hoodie.sql.insert.mode= strict")
+
+ val tableName2 = generateTableName
Review comment:
Yes, will add the case for multi-level partition
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] pengzhiwei2018 edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-894613109
Hi @nsivabalan , The PR has updated with the follow chanes:
add "upsert" mode for insert.mode. Currently we have 3 insert mode:
- upsert
In upsert mode for insert into, duplicate record on primary key will be updated.This is the default insert mode for pk-table.
- strict
In strict mode for insert into, we do the pk uniqueness guarantee for COW pk-table. For MOR pk-table, it has the same behavior with "upsert" mode.
- non-strict
In non-strict mode for insert into, we use insert operation to write data which allow writing the duplicate record.
The default insert mode is `upsert`.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] pengzhiwei2018 commented on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-894613775
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[GitHub] [hudi] nsivabalan commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r683843426
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
+ // insert overwrite table
+ case (_, _, true, _) if !isPartitionedTable => INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
+ // if the table has primaryKey and the dropDuplicate has disable, use the upsert operation
+ case (true, false, false, false) => UPSERT_OPERATION_OPT_VAL
+ // if enableBulkInsert is true and the table is non-primaryKeyed, use the bulk insert operation
+ case (false, true, _, _) => BULK_INSERT_OPERATION_OPT_VAL
+ // for the rest case, use the insert operation
+ case (_, _, _, _) => INSERT_OPERATION_OPT_VAL
Review comment:
I did go through every case here and have 2 suggestions. rest of the cases looks good. You don't need to consider my proposal above. But would like you to consider below feedback.
1.
```
case (true, true, _, _) if !isNonStrictMode => throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert in strict mode.")
```
Can we enable preCombine here and proceed with Bulk_Insert operation. Within hudi, we can do preCombine/dedup. As we agreed on using bulk_insert as default with CTAS, this will be a very common use-case.
2.
```
case (_, true, true, _) if isPartitionedTable =>
throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
```
since we agreed on enabling Bulk_insert as default for CTAS, this will be very common use-case as well. Can you help me understand why do we fail this call? why can't we let it proceed. This is basically, CTAS for a partitioned table.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/HoodieSparkSqlWriter.scala
##########
@@ -159,7 +159,10 @@ object HoodieSparkSqlWriter {
// Convert to RDD[HoodieRecord]
val genericRecords: RDD[GenericRecord] = HoodieSparkUtils.createRdd(df, schema, structName, nameSpace)
- val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean || operation.equals(WriteOperationType.UPSERT);
+ val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean ||
+ operation.equals(WriteOperationType.UPSERT) ||
+ parameters.getOrElse(HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key(),
Review comment:
my bad. I get it now.
If InsertDropDups is set, we automatically set combine.before.insert. but if a user has set just "combine.before.insert", we need to do PreCombine here.
But I am not sure why this wasn't reported by anyone until now.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] vinothchandar commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
vinothchandar commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r682108786
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
Review comment:
insert overwrite partition should be using the `INSERT_OVERWRITE` operation.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/HoodieSparkSqlWriter.scala
##########
@@ -159,7 +159,10 @@ object HoodieSparkSqlWriter {
// Convert to RDD[HoodieRecord]
val genericRecords: RDD[GenericRecord] = HoodieSparkUtils.createRdd(df, schema, structName, nameSpace)
- val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean || operation.equals(WriteOperationType.UPSERT);
+ val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean ||
+ operation.equals(WriteOperationType.UPSERT) ||
+ parameters.getOrElse(HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key(),
Review comment:
@pengzhiwei2018 do you agree with siva's analysis above?
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
Review comment:
+1 users might have another hudi table for e.g to CTAS from. So if we disallow bulk insert with a pk, then there is no good way to do a full bootstrap. Can we relax this?
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
+ // insert overwrite table
+ case (_, _, true, _) if !isPartitionedTable => INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
+ // if the table has primaryKey and the dropDuplicate has disable, use the upsert operation
+ case (true, false, false, false) => UPSERT_OPERATION_OPT_VAL
+ // if enableBulkInsert is true and the table is non-primaryKeyed, use the bulk insert operation
+ case (false, true, _, _) => BULK_INSERT_OPERATION_OPT_VAL
+ // for the rest case, use the insert operation
+ case (_, _, _, _) => INSERT_OPERATION_OPT_VAL
Review comment:
having configs to control sql behavior sounds pretty complex to me. Can we just pick the right operation for each type.
##########
File path: hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/DataSourceOptions.scala
##########
@@ -248,6 +248,14 @@ object DataSourceWriteOptions {
.withDocumentation("When set to true, will perform write operations directly using the spark native " +
"`Row` representation, avoiding any additional conversion costs.")
+ /**
+ * Enable the bulk insert for sql insert statement.
+ */
+ val SQL_ENABLE_BULK_INSERT:ConfigProperty[String] = ConfigProperty
Review comment:
CTAS should use bulk_insert and insert into should use regular inserts IMO.
lets please not add more configs like this proactively. We can get user feedback and iterate.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
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URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] leesf commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
leesf commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r677534597
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -243,6 +256,8 @@ object InsertIntoHoodieTableCommand {
RECORDKEY_FIELD_OPT_KEY.key -> primaryColumns.mkString(","),
PARTITIONPATH_FIELD_OPT_KEY.key -> partitionFields,
PAYLOAD_CLASS_OPT_KEY.key -> payloadClassName,
+ ENABLE_ROW_WRITER_OPT_KEY.key -> enableBulkInsert.toString,
+ HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key -> isPrimaryKeyTable.toString, // if the table has primaryKey, enable the combine
Review comment:
even for pk-table, in insert mode, there is no need to combine the input, right?
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] pengzhiwei2018 commented on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-894651032
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
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[GitHub] [hudi] nsivabalan commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r684894126
##########
File path: hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/TestInsertTable.scala
##########
@@ -378,6 +379,41 @@ class TestInsertTable extends TestHoodieSqlBase {
Seq(1, "a1", 10.0, "2021-07-18"),
Seq(2, "a2", 10.0, "2021-07-18")
)
+
+ // Test bulk insert for multi-level partition
+ val tableMultiPartition = generateTableName
+ spark.sql(
+ s"""
+ |create table $tableMultiPartition (
+ | id int,
+ | name string,
+ | price double,
+ | dt string,
+ | hh string
+ |) using hudi
+ | options (
+ | type = '$tableType'
+ | )
+ | partitioned by (dt, hh)
+ | location '${tmp.getCanonicalPath}/$tableMultiPartition'
+ """.stripMargin)
+
+ // Enable the bulk insert
+ spark.sql("set hoodie.sql.bulk.insert.enable = true")
+ spark.sql(s"insert into $tableMultiPartition values(1, 'a1', 10, '2021-07-18', '12')")
+
+ checkAnswer(s"select id, name, price, dt, hh from $tableMultiPartition")(
Review comment:
lets verify meta fields as well as suggested in other patch.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
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[GitHub] [hudi] leesf commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
leesf commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r674869873
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/HoodieOptionConfig.scala
##########
@@ -172,6 +178,15 @@ object HoodieOptionConfig {
params.get(DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY.key)
}
+ /**
+ * Whether enable the bulk insert for sql insert statement when there is no primaryKey in the table.
+ */
+ def enableBulkInsert(options: Map[String, String]): Boolean = {
Review comment:
ENABLE_ROW_WRITER_OPT_KEY is a different type of bulk_insert, spark sql support both types?
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[GitHub] [hudi] pengzhiwei2018 commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r678031341
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/HoodieSparkSqlWriter.scala
##########
@@ -159,7 +159,10 @@ object HoodieSparkSqlWriter {
// Convert to RDD[HoodieRecord]
val genericRecords: RDD[GenericRecord] = HoodieSparkUtils.createRdd(df, schema, structName, nameSpace)
- val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean || operation.equals(WriteOperationType.UPSERT);
+ val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean ||
+ operation.equals(WriteOperationType.UPSERT) ||
+ parameters.getOrElse(HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key(),
Review comment:
If the `COMBINE_BEFORE_INSERT_PROP` has enabled, `SparkInsertCommitActionExecutor` will do the `combineOnCondition` in `AbstractWriteHelper` which will need the `precombine` value .
But here we have ignored the case of `COMBINE_BEFORE_INSERT_PROP` which will not extract the `precombine` value to the HoodiePayload.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
Review comment:
Because currently we will do the primary key uniqueness check when inserting data to the pk-table, just like what database does. Bulk insert currently cannot do such things.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -243,6 +256,8 @@ object InsertIntoHoodieTableCommand {
RECORDKEY_FIELD_OPT_KEY.key -> primaryColumns.mkString(","),
PARTITIONPATH_FIELD_OPT_KEY.key -> partitionFields,
PAYLOAD_CLASS_OPT_KEY.key -> payloadClassName,
+ ENABLE_ROW_WRITER_OPT_KEY.key -> enableBulkInsert.toString,
+ HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key -> isPrimaryKeyTable.toString, // if the table has primaryKey, enable the combine
Review comment:
We need to ensure that data is unique for pk-table just like database, so I do combine for the input.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] nsivabalan commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r680197209
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
Review comment:
anyways, we can call it out that its responsibility of the user to ensure there are uniqueness. Also, IIUC, hudi can handle duplicates. Incase of updates, both records will be updated. but bulk_insert is very performant compared to regular Insert especially w/ row wirter. So, we should not keep it too restrictive for use. I know from the community msgs, that lot of users leverage bulk_insert. I would vote to relax this constraint.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] pengzhiwei2018 commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r674875373
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/HoodieOptionConfig.scala
##########
@@ -172,6 +178,15 @@ object HoodieOptionConfig {
params.get(DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY.key)
}
+ /**
+ * Whether enable the bulk insert for sql insert statement when there is no primaryKey in the table.
+ */
+ def enableBulkInsert(options: Map[String, String]): Boolean = {
Review comment:
I saw that currently ENABLE_ROW_WRITER_OPT_KEY is only used for bulk insert, so i reused this config.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/HoodieSparkSqlWriter.scala
##########
@@ -159,7 +159,10 @@ object HoodieSparkSqlWriter {
// Convert to RDD[HoodieRecord]
val genericRecords: RDD[GenericRecord] = HoodieSparkUtils.createRdd(df, schema, structName, nameSpace)
- val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean || operation.equals(WriteOperationType.UPSERT);
+ val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean ||
+ operation.equals(WriteOperationType.UPSERT) ||
+ parameters.getOrElse(HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key(),
Review comment:
Yes, if we have enable the COMBINE_BEFORE_INSERT_PROP for insert, it has not compute the pre combine field value which will result incorrect result for insert with duplicate records.
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] leesf commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
leesf commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r677534597
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -243,6 +256,8 @@ object InsertIntoHoodieTableCommand {
RECORDKEY_FIELD_OPT_KEY.key -> primaryColumns.mkString(","),
PARTITIONPATH_FIELD_OPT_KEY.key -> partitionFields,
PAYLOAD_CLASS_OPT_KEY.key -> payloadClassName,
+ ENABLE_ROW_WRITER_OPT_KEY.key -> enableBulkInsert.toString,
+ HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key -> isPrimaryKeyTable.toString, // if the table has primaryKey, enable the combine
Review comment:
for pk-table and in insert mode, there is no need to combine the input, right?
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] pengzhiwei2018 commented on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-894613109
Hi @nsivabalan , The PR has updated with the follow chanes:
add "upsert" mode for insert.mode. Currently we have 3 insert mode:
- upsert
In upsert mode for insert into, duplicate record on primary key will be updated.This is the default insert mode for pk-table.
- strict
In strict mode for insert into, we do the pk uniqueness guarantee for COW pk-table. For MOR pk-table, it has the same behavior with "upsert" mode.
- non-strict
In non-strict mode for insert into, we use insert operation to write data which allow writing the duplicate record.
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[GitHub] [hudi] pengzhiwei2018 commented on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 commented on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-894753661
@hudi-bot run azure
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[GitHub] [hudi] leesf commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
leesf commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r674872620
##########
File path: hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/TestInsertTable.scala
##########
@@ -144,7 +145,7 @@ class TestInsertTable extends TestHoodieSqlBase {
| partitioned by (dt)
| location '${tmp.getCanonicalPath}/$tableName'
""".stripMargin)
-
+ spark.sql("set hoodie.datasource.write.row.writer.enable = false")
Review comment:
all set to false?
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[GitHub] [hudi] nsivabalan commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
nsivabalan commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r680186620
##########
File path: hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/DataSourceOptions.scala
##########
@@ -248,6 +248,14 @@ object DataSourceWriteOptions {
.withDocumentation("When set to true, will perform write operations directly using the spark native " +
"`Row` representation, avoiding any additional conversion costs.")
+ /**
+ * Enable the bulk insert for sql insert statement.
+ */
+ val SQL_ENABLE_BULK_INSERT:ConfigProperty[String] = ConfigProperty
Review comment:
@vinothchandar : In sql, we don't have two separate commands like INSERT into and BULK_INSERT into. so, guess we are going this route. But default CTAS choose INSERT operation. I am thinking users may not use bulk_insert only since they have to set the property explicitly. any thoughts.
There are two things to discuss.
1. Which operation to use with CTAS
2. which operation to use with INSERT into.
State as of now, is "Insert". And user has to explicitly set operation type to bulk_insert before calling any of this commands.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
+ // insert overwrite table
+ case (_, _, true, _) if !isPartitionedTable => INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
Review comment:
HoodieSparkSqlWriter will handle this save mode.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
+ // insert overwrite table
+ case (_, _, true, _) if !isPartitionedTable => INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
+ // if the table has primaryKey and the dropDuplicate has disable, use the upsert operation
+ case (true, false, false, false) => UPSERT_OPERATION_OPT_VAL
+ // if enableBulkInsert is true and the table is non-primaryKeyed, use the bulk insert operation
+ case (false, true, _, _) => BULK_INSERT_OPERATION_OPT_VAL
+ // for the rest case, use the insert operation
+ case (_, _, _, _) => INSERT_OPERATION_OPT_VAL
Review comment:
Here is my thought on choosing the right operation. Having too many case statements might complicate things and is error prone too. As I mentioned earlier, we should try to do any valid conversions in HoodiesSparkSqlWriter. Only those thats applicable just to sql dml, we should keep it here.
Anyways, here is one simplified approach. Ignoring the primary, non primary key table for now. We can come back to that later once we have consensus on this.
We need just two configs.
hoodie.sql.enable.bulk_insert (default false)
hoodie.sql.overwrite.entire.table (default true)
From sql syntax, there are two commands allowed.
"INSERT" into and "INSERT OVERWRITE".
"INSERT" with no other configs set -> insert operation
"INSERT" with enable bulk insert set -> bulk_insert
"INSERT OVERWRITE" with no other configs set -> insert_overwrite_table operation
"INSERT OVERWRITE" with hoodie.sql.overwrite.entire.table = false -> insert_overwrite operation.
"INSERT OVERWRITE" with enable bulk_insert set -> bulk_insert. pass the right save mode to HoodieSparkSqlWriter
"INSERT OVERWRITE" with enable bulk_insert set and hoodie.sql.overwrite.entire.table = false -> bulk_insert. pass the right save mode to HoodieSparkSqlWriter.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
Review comment:
lets say a user is doing something like this.
- create hudi table w/ primary key and partition col set.
- does bulk_insert with overwrite.
Do we fail this command? This is very common use-case. Not sure how we can fail this.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
+ // insert overwrite table
+ case (_, _, true, _) if !isPartitionedTable => INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
+ // if the table has primaryKey and the dropDuplicate has disable, use the upsert operation
+ case (true, false, false, false) => UPSERT_OPERATION_OPT_VAL
Review comment:
again trying to understand why we do this. If someone is explicitly issuing "INSERT" into, we should try to use "insert" operation. Why switching to "upsert" just for primary keyed table ? can you please clarify
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
Review comment:
This is already taken care in HoodieSparkSqlWriter. Don't think we need to validate this here.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -243,6 +256,8 @@ object InsertIntoHoodieTableCommand {
RECORDKEY_FIELD_OPT_KEY.key -> primaryColumns.mkString(","),
PARTITIONPATH_FIELD_OPT_KEY.key -> partitionFields,
PAYLOAD_CLASS_OPT_KEY.key -> payloadClassName,
+ ENABLE_ROW_WRITER_OPT_KEY.key -> enableBulkInsert.toString,
+ HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key -> isPrimaryKeyTable.toString, // if the table has primaryKey, enable the combine
Review comment:
yeah, I am also not sure on this. We will do a preCombine step for any INSERT in general. wondering why not let users take up the responsibility.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
+ // insert overwrite partition
+ case (_, _, true, _) if isPartitionedTable => INSERT_OVERWRITE_OPERATION_OPT_VAL
Review comment:
not sure if we can do this.
If user has set "overwrite" for a partitioned table, here we are overwriting only the interested partition and not the entire table. Is that a common sql expectation? What incase a user has a partitioned table and wants to overwrite an entire table?
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
Review comment:
anyways, we can all it out that its responsibility of the user to ensure there are uniqueness. Also, IIUC, hudi can handle duplicates. Incase of updates, both records will be updated. but bulk_insert is very performant compared to regular Insert especially w/ row wirter. So, we should not keep it too restrictive for use. I know from the community msgs, that lot of users leverage bulk_insert. I would vote to relax this constraint.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/hudi/HoodieSparkSqlWriter.scala
##########
@@ -159,7 +159,10 @@ object HoodieSparkSqlWriter {
// Convert to RDD[HoodieRecord]
val genericRecords: RDD[GenericRecord] = HoodieSparkUtils.createRdd(df, schema, structName, nameSpace)
- val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean || operation.equals(WriteOperationType.UPSERT);
+ val shouldCombine = parameters(INSERT_DROP_DUPS_OPT_KEY.key()).toBoolean ||
+ operation.equals(WriteOperationType.UPSERT) ||
+ parameters.getOrElse(HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key(),
Review comment:
I digged in to understand this. Actually INSERT_DROP_DUPS_OPT_KEY is used at the Dataource layer and COMBINE_BEFORE_INSERT_PROP is used in writeClient layer. In other words, both are referring to same config only. [DataSourceUtils](https://github.com/apache/hudi/blob/6353fc865f43854e0e185af33e8ad091c8870d78/hudi-spark-datasource/hudi-spark-common/src/main/java/org/apache/hudi/DataSourceUtils.java#L178) converts INSERT_DROP_DUPS_OPT_KEY's value as COMBINE_BEFORE_INSERT_PROP.
So, don't think we need to check both INSERT_DROP_DUPS_OPT_KEY and COMBINE_BEFORE_INSERT_PROP.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
Review comment:
hmmm, interesting. I didn't know we do uniqueness check for inserts with primary keyed table.
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -209,19 +209,32 @@ object InsertIntoHoodieTableCommand {
.getOrElse(INSERT_DROP_DUPS_OPT_KEY.defaultValue)
.toBoolean
- val operation = if (isOverwrite) {
- if (table.partitionColumnNames.nonEmpty) {
- INSERT_OVERWRITE_OPERATION_OPT_VAL // overwrite partition
- } else {
- INSERT_OPERATION_OPT_VAL
+ val enableBulkInsert = parameters.getOrElse(DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.key,
+ DataSourceWriteOptions.SQL_ENABLE_BULK_INSERT.defaultValue()).toBoolean
+ val isPartitionedTable = table.partitionColumnNames.nonEmpty
+ val isPrimaryKeyTable = primaryColumns.nonEmpty
+ val operation =
+ (isPrimaryKeyTable, enableBulkInsert, isOverwrite, dropDuplicate) match {
+ case (true, true, _, _) =>
+ throw new IllegalArgumentException(s"Table with primaryKey can not use bulk insert.")
+ case (_, true, true, _) if isPartitionedTable =>
+ throw new IllegalArgumentException(s"Insert Overwrite Partition can not use bulk insert.")
+ case (_, true, _, true) =>
+ throw new IllegalArgumentException(s"Bulk insert cannot support drop duplication." +
+ s" Please disable $INSERT_DROP_DUPS_OPT_KEY and try again.")
+ // if enableBulkInsert is true, use bulk insert for the insert overwrite non-partitioned table.
+ case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
Review comment:
```
case (_, true, true, _) if !isPartitionedTable => BULK_INSERT_OPERATION_OPT_VAL
```
Already the operation is bulk_insert right(2nd arg). Not sure why do we need this case?
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[GitHub] [hudi] leesf commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
leesf commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r676541180
##########
File path: hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/DataSourceOptions.scala
##########
@@ -247,6 +247,13 @@ object DataSourceWriteOptions {
.defaultValue("false")
.withDocumentation("When set to true, will perform write operations directly using the spark native " +
"`Row` representation, avoiding any additional conversion costs.")
+ /**
+ * Enable the bulk insert for sql insert statement.
+ */
+ val SQL_ENABLE_BULK_INSERT:ConfigProperty[String] = ConfigProperty
+ .key("hoodie.sq.bulk.insert.enable")
Review comment:
nit: sql
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] leesf commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
leesf commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r676542684
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -243,6 +256,8 @@ object InsertIntoHoodieTableCommand {
RECORDKEY_FIELD_OPT_KEY.key -> primaryColumns.mkString(","),
PARTITIONPATH_FIELD_OPT_KEY.key -> partitionFields,
PAYLOAD_CLASS_OPT_KEY.key -> payloadClassName,
+ ENABLE_ROW_WRITER_OPT_KEY.key -> enableBulkInsert.toString,
+ HoodieWriteConfig.COMBINE_BEFORE_INSERT_PROP.key -> isPrimaryKeyTable.toString, // if the table has primaryKey, enable the combine
Review comment:
why the table has primaryKey, should enable the combine?
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] leesf commented on a change in pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
leesf commented on a change in pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#discussion_r677536750
##########
File path: hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/InsertIntoHoodieTableCommand.scala
##########
@@ -243,6 +256,8 @@ object InsertIntoHoodieTableCommand {
RECORDKEY_FIELD_OPT_KEY.key -> primaryColumns.mkString(","),
PARTITIONPATH_FIELD_OPT_KEY.key -> partitionFields,
PAYLOAD_CLASS_OPT_KEY.key -> payloadClassName,
+ ENABLE_ROW_WRITER_OPT_KEY.key -> enableBulkInsert.toString,
Review comment:
so here why there is no option for bulk_insert without row_writer? must in row_writer?
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] hudi-bot edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
hudi-bot edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-884869427
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[GitHub] [hudi] pengzhiwei2018 edited a comment on pull request #3328: [HUDI-2208] Support Bulk Insert For Spark Sql
Posted by GitBox <gi...@apache.org>.
pengzhiwei2018 edited a comment on pull request #3328:
URL: https://github.com/apache/hudi/pull/3328#issuecomment-894613109
Hi @nsivabalan , The PR has updated with the follow chanes:
add "upsert" mode for insert.mode. Currently we have 3 insert mode:
- upsert
In upsert mode for insert into, duplicate record on primary key will be updated.This is the default insert mode for pk-table.
- strict
In strict mode for insert into, we do the pk uniqueness guarantee for COW pk-table. For MOR pk-table, it has the same behavior with "upsert" mode.
- non-strict
In non-strict mode for insert into, we use insert operation to write data which allow writing the duplicate record.
The default insert mode is `upsert` for pk-table. And these config is only used to control the behavior of pk-table. For non pk-table, the insert operation is always `insert` or `bulkinsert`
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