pan3793 opened a new pull request, #53624:
URL: https://github.com/apache/spark/pull/53624
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### What changes were proposed in this pull request?
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This PR moves `hive.exec.max.dynamic.partitions` check from the hive side to
the spark side, also assigns the error condition `_LEGACY_ERROR_TEMP_2277` with
a proper name `DYNAMIC_PARTITION_WRITE_PARTITION_NUM_LIMIT_EXCEEDED`
### Why are the changes needed?
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1. If you propose a new API, clarify the use case for a new API.
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SPARK-37217 partially handles `hive.exec.max.dynamic.partitions` on the
spark side, but only for `INSERT OVERWRITE` case on performing dynamic
partition overwrite to an external Hive SerDe table, which reduces the data
loss risks but still has risks, e.g. when the user updates(especially
increases) the session conf `hive.exec.max.dynamic.partitions`, it only takes
effect on the spark side, the shared `Hive` still uses a static hadoop conf
from `sc.newHadoopConf`, thus if the user hits the error and increases the
value by following the error message's suggestion, it can pass the spark side
check but fail on the hive side later, then data loss issue mentioned in
SPARK-37217 will happens again.
Currently, the following three frequently used configs related to dynamic
partition overwrite for Hive SerDe tables have inconsistent behaviors
```
-- this works
SET hive.exec.dynamic.partition=true;
-- this also works
SET hive.exec.dynamic.partition.mode=nonstrict;
-- this does not work, but the error message suggests the user to do that
SET hive.exec.max.dynamic.partitions=1001;
```
```
Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: Number of
dynamic partitions created is 3, which is more than 2. To solve this try to set
hive.exec.max.dynamic.partitions to at least 3.
at
org.apache.hadoop.hive.ql.metadata.Hive.getValidPartitionsInPath(Hive.java:1862)
at
org.apache.hadoop.hive.ql.metadata.Hive.loadDynamicPartitions(Hive.java:1902)
at
java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77)
at
java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:569)
at
org.apache.spark.sql.hive.client.Shim_v2_1.loadDynamicPartitions(HiveShim.scala:1110)
at
org.apache.spark.sql.hive.client.HiveClientImpl.$anonfun$loadDynamicPartitions$1(HiveClientImpl.scala:1013)
at
scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.scala:18)
at
org.apache.spark.sql.hive.client.HiveClientImpl.$anonfun$withHiveState$1(HiveClientImpl.scala:294)
at
org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:237)
at
org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:236)
at
org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:274)
at
org.apache.spark.sql.hive.client.HiveClientImpl.loadDynamicPartitions(HiveClientImpl.scala:1004)
at
org.apache.spark.sql.hive.HiveExternalCatalog.$anonfun$loadDynamicPartitions$1(HiveExternalCatalog.scala:1051)
at
scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.scala:18)
at
org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:105)
at
org.apache.spark.sql.hive.HiveExternalCatalog.loadDynamicPartitions(HiveExternalCatalog.scala:1031)
...
```
### Does this PR introduce _any_ user-facing change?
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Yes, with this change, users are allowed to set
`hive.exec.max.dynamic.partitions` in session conf, e.g., by executing `SET
hive.exec.max.dynamic.partitions=1001`, and users will see more consistent
behavior on `hive.exec.max.dynamic.partitions` checks, it always perform checks
before calling external catalog `loadDynamicPartitions`, for both managed and
external table, and both `INSERT INTO` and `INSERT OVERWRITE` dynamic partition
write operation for Hive SerDe tables.
### How was this patch tested?
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New UT is added.
### Was this patch authored or co-authored using generative AI tooling?
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No.
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