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Posted to reviews@spark.apache.org by "khalidmammadov (via GitHub)" <gi...@apache.org> on 2023/02/27 19:42:34 UTC
[GitHub] [spark] khalidmammadov opened a new pull request, #40015: [SPARK-42437][PySpark][Connect] PySpark catalog.cacheTable will allow to specify storage level
khalidmammadov opened a new pull request, #40015:
URL: https://github.com/apache/spark/pull/40015
Currently PySpark version of `catalog.cacheTable` function does not support to specify storage level. This is to add that.
After changes:
## Spark Connect
```
bin/pyspark --remote "local[*]"
Python 3.9.5 (default, Nov 23 2021, 15:27:38)
[GCC 9.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
23/02/17 20:41:07 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/__ / .__/\_,_/_/ /_/\_\ version 3.5.0.dev0
/_/
Using Python version 3.9.5 (default, Nov 23 2021 15:27:38)
Client connected to the Spark Connect server at localhost
SparkSession available as 'spark'.
>>> spark.range(1).write.saveAsTable("tab1", format="csv", mode="overwrite")
>>> spark.catalog.listTables()
[Table(name='tab1', catalog='spark_catalog', namespace=['default'], description=None, tableType='MANAGED', isTemporary=False)]
>>> spark.catalog.cacheTable("tab1")
>>> spark.catalog.isCached("tab1")
True
>>> spark.catalog.clearCache()
>>> spark.catalog.isCached("tab1")
False
>>> from pyspark.storagelevel import StorageLevel
>>> spark.catalog.cacheTable("tab1", StorageLevel.OFF_HEAP)
>>> spark.catalog.isCached("tab1")
True
```
## PySpark
```
/home/spark# bin/pyspark
Python 3.9.5 (default, Nov 23 2021, 15:27:38)
[GCC 9.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
23/02/17 20:43:46 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/__ / .__/\_,_/_/ /_/\_\ version 3.5.0-SNAPSHOT
/_/
Using Python version 3.9.5 (default, Nov 23 2021 15:27:38)
Spark context Web UI available at http://localhost:4040
Spark context available as 'sc' (master = local[*], app id = local-1676666626670).
SparkSession available as 'spark'.
>>> spark.range(1).write.saveAsTable("tab2", format="csv", mode="overwrite")
>>> spark.catalog.listTables()
[Table(name='tab2', catalog='spark_catalog', namespace=['default'], description=None, tableType='MANAGED', isTemporary=False)]
>>> spark.catalog.cacheTable("tab2")
>>>
>>> spark.catalog.isCached("tab2")
True
>>> spark.catalog.clearCache()
>>> spark.catalog.isCached("tab2")
False
>>> from pyspark.storagelevel import StorageLevel
>>> spark.catalog.cacheTable("tab2", StorageLevel.OFF_HEAP)
>>> spark.catalog.isCached("tab2")
True
```
### What changes were proposed in this pull request?
Add extra parameter to catalog.cacheTable
### Why are the changes needed?
To allow users specify which storage level to use in cache in PySpark/Connect code
### Does this PR introduce _any_ user-facing change?
Yes
### How was this patch tested?
Updated existing test cases
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[GitHub] [spark] khalidmammadov commented on pull request #40015: [SPARK-42437][PySpark][Connect] PySpark catalog.cacheTable will allow to specify storage level
Posted by "khalidmammadov (via GitHub)" <gi...@apache.org>.
khalidmammadov commented on PR #40015:
URL: https://github.com/apache/spark/pull/40015#issuecomment-1435639551
@HyukjinKwon can you please check if it looks Ok?
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[GitHub] [spark] khalidmammadov commented on pull request #40015: [SPARK-42437][PYSPARK][CONNECT] PySpark catalog.cacheTable will allow to specify storage level
Posted by "khalidmammadov (via GitHub)" <gi...@apache.org>.
khalidmammadov commented on PR #40015:
URL: https://github.com/apache/spark/pull/40015#issuecomment-1495403951
Hi, thanks for letting me know. I will look at it
On Mon, 3 Apr 2023, 21:15 Takuya UESHIN, ***@***.***> wrote:
> Hi @khalidmammadov <https://github.com/khalidmammadov>, now that Catalog
> in Scala client including protobuf definition has been implemented, do you
> want to continue working on this?
> Otherwise, I can take this over.
> Thanks.
>
> —
> Reply to this email directly, view it on GitHub
> <https://github.com/apache/spark/pull/40015#issuecomment-1494921787>, or
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[GitHub] [spark] khalidmammadov commented on a diff in pull request #40015: [SPARK-42437][PYTHON][CONNECT] PySpark catalog.cacheTable will allow to specify storage level
Posted by "khalidmammadov (via GitHub)" <gi...@apache.org>.
khalidmammadov commented on code in PR #40015:
URL: https://github.com/apache/spark/pull/40015#discussion_r1161268454
##########
python/pyspark/sql/connect/plan.py:
##########
@@ -1830,14 +1831,24 @@ def plan(self, session: "SparkConnectClient") -> proto.Relation:
class CacheTable(LogicalPlan):
- def __init__(self, table_name: str) -> None:
+ def __init__(self, table_name: str, storage_level: Optional[StorageLevel] = None) -> None:
super().__init__(None)
self._table_name = table_name
-
- def plan(self, session: "SparkConnectClient") -> proto.Relation:
- plan = proto.Relation(
- catalog=proto.Catalog(cache_table=proto.CacheTable(table_name=self._table_name))
- )
+ self._storage_level = storage_level
+
+ def plan(self, session: "SparkConnectClient") -> proto.Relation:
+ _cache_table = proto.CacheTable(table_name=self._table_name)
+ if self._storage_level:
+ _cache_table.storage_level.CopyFrom(
+ proto.StorageLevel(
+ use_disk=self._storage_level.useDisk,
+ use_memory=self._storage_level.useMemory,
+ use_off_heap=self._storage_level.useOffHeap,
+ deserialized=self._storage_level.deserialized,
+ replication=self._storage_level.replication,
+ )
Review Comment:
Shall we do this as a follow up, rather than here?
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[GitHub] [spark] khalidmammadov commented on pull request #40015: [SPARK-42437][PySpark][Connect] PySpark catalog.cacheTable will allow to specify storage level
Posted by "khalidmammadov (via GitHub)" <gi...@apache.org>.
khalidmammadov commented on PR #40015:
URL: https://github.com/apache/spark/pull/40015#issuecomment-1441644663
Closing as no traction
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[GitHub] [spark] HyukjinKwon commented on pull request #40015: [SPARK-42437][PySpark][Connect] PySpark catalog.cacheTable will allow to specify storage level
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on PR #40015:
URL: https://github.com/apache/spark/pull/40015#issuecomment-1442772377
Sorry for late responses. We should better have this feature parity. But I need to check w/ the concern about storage level (raised internally). I will ping the guy to comment here.
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[GitHub] [spark] khalidmammadov commented on pull request #40015: [SPARK-42437][PYTHON][CONNECT] PySpark catalog.cacheTable will allow to specify storage level
Posted by "khalidmammadov (via GitHub)" <gi...@apache.org>.
khalidmammadov commented on PR #40015:
URL: https://github.com/apache/spark/pull/40015#issuecomment-1505902017
Thanks @ueshin!
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[GitHub] [spark] khalidmammadov commented on pull request #40015: [SPARK-42437][PYTHON][CONNECT] PySpark catalog.cacheTable will allow to specify storage level
Posted by "khalidmammadov (via GitHub)" <gi...@apache.org>.
khalidmammadov commented on PR #40015:
URL: https://github.com/apache/spark/pull/40015#issuecomment-1501103732
The build was failing due to https://github.com/apache/spark/pull/40674 and now fixed by https://github.com/apache/spark/pull/40681
Rebased.
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[GitHub] [spark] ueshin closed pull request #40015: [SPARK-42437][PYTHON][CONNECT] PySpark catalog.cacheTable will allow to specify storage level
Posted by "ueshin (via GitHub)" <gi...@apache.org>.
ueshin closed pull request #40015: [SPARK-42437][PYTHON][CONNECT] PySpark catalog.cacheTable will allow to specify storage level
URL: https://github.com/apache/spark/pull/40015
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[GitHub] [spark] ueshin commented on a diff in pull request #40015: [SPARK-42437][PYTHON][CONNECT] PySpark catalog.cacheTable will allow to specify storage level
Posted by "ueshin (via GitHub)" <gi...@apache.org>.
ueshin commented on code in PR #40015:
URL: https://github.com/apache/spark/pull/40015#discussion_r1160908837
##########
python/pyspark/sql/connect/plan.py:
##########
@@ -1830,14 +1831,24 @@ def plan(self, session: "SparkConnectClient") -> proto.Relation:
class CacheTable(LogicalPlan):
- def __init__(self, table_name: str) -> None:
+ def __init__(self, table_name: str, storage_level: Optional[StorageLevel] = None) -> None:
super().__init__(None)
self._table_name = table_name
-
- def plan(self, session: "SparkConnectClient") -> proto.Relation:
- plan = proto.Relation(
- catalog=proto.Catalog(cache_table=proto.CacheTable(table_name=self._table_name))
- )
+ self._storage_level = storage_level
+
+ def plan(self, session: "SparkConnectClient") -> proto.Relation:
+ _cache_table = proto.CacheTable(table_name=self._table_name)
+ if self._storage_level:
+ _cache_table.storage_level.CopyFrom(
+ proto.StorageLevel(
+ use_disk=self._storage_level.useDisk,
+ use_memory=self._storage_level.useMemory,
+ use_off_heap=self._storage_level.useOffHeap,
+ deserialized=self._storage_level.deserialized,
+ replication=self._storage_level.replication,
+ )
Review Comment:
Shall we extract functions to convert to/from `proto.StorageLevel` and reuse them in `client.py` as well?
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[GitHub] [spark] khalidmammadov commented on a diff in pull request #40015: [SPARK-42437][PySpark][Connect] PySpark catalog.cacheTable will allow to specify storage level
Posted by "khalidmammadov (via GitHub)" <gi...@apache.org>.
khalidmammadov commented on code in PR #40015:
URL: https://github.com/apache/spark/pull/40015#discussion_r1125615556
##########
connector/connect/common/src/main/protobuf/spark/connect/types.proto:
##########
@@ -184,3 +184,15 @@ message DataType {
DataType sql_type = 5;
}
}
+
+enum StorageLevel {
Review Comment:
@zhengruifeng thanks for review.
I have removed enum and static mappings.
Now, storage level is resolved based on user input. It allows Python users to use PySpark constants or customise if needed. This the same logic how PySpark accepts and resolves storage level from user.
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[GitHub] [spark] khalidmammadov commented on pull request #40015: [SPARK-42437][PySpark][Connect] PySpark catalog.cacheTable will allow to specify storage level
Posted by "khalidmammadov (via GitHub)" <gi...@apache.org>.
khalidmammadov commented on PR #40015:
URL: https://github.com/apache/spark/pull/40015#issuecomment-1444167507
Thanks @HyukjinKwon
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[GitHub] [spark] ueshin commented on pull request #40015: [SPARK-42437][PYSPARK][CONNECT] PySpark catalog.cacheTable will allow to specify storage level
Posted by "ueshin (via GitHub)" <gi...@apache.org>.
ueshin commented on PR #40015:
URL: https://github.com/apache/spark/pull/40015#issuecomment-1494921787
Hi @khalidmammadov, now that `Catalog` in Scala client including protobuf definition has been implemented, do you want to continue working on this?
Otherwise, I can take this over.
Thanks.
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[GitHub] [spark] ueshin commented on a diff in pull request #40015: [SPARK-42437][PYTHON][CONNECT] PySpark catalog.cacheTable will allow to specify storage level
Posted by "ueshin (via GitHub)" <gi...@apache.org>.
ueshin commented on code in PR #40015:
URL: https://github.com/apache/spark/pull/40015#discussion_r1163280656
##########
python/pyspark/sql/catalog.py:
##########
@@ -917,25 +919,34 @@ def isCached(self, tableName: str) -> bool:
"""
return self._jcatalog.isCached(tableName)
- def cacheTable(self, tableName: str) -> None:
- """Caches the specified table in-memory.
+ def cacheTable(self, tableName: str, storageLevel: Optional[StorageLevel] = None) -> None:
+ """Caches the specified table in-memory or with given storage level.
+ Default MEMORY_AND_DISK.
.. versionadded:: 2.0.0
Parameters
----------
tableName : str
name of the table to get.
+ storageLevel : :class:`StorageLevel`
+ storage level to set for persistence.
.. versionchanged:: 3.4.0
Allow ``tableName`` to be qualified with catalog name.
+ .. versionchanged:: 3.5.0
+ Allow to specify storage level.
Review Comment:
```suggestion
tableName : str
name of the table to get.
.. versionchanged:: 3.4.0
Allow ``tableName`` to be qualified with catalog name.
storageLevel : :class:`StorageLevel`
storage level to set for persistence.
.. versionchanged:: 3.5.0
Allow to specify storage level.
```
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[GitHub] [spark] khalidmammadov commented on pull request #40015: [SPARK-42437][PySpark][Connect] PySpark catalog.cacheTable will allow to specify storage level
Posted by "khalidmammadov (via GitHub)" <gi...@apache.org>.
khalidmammadov commented on PR #40015:
URL: https://github.com/apache/spark/pull/40015#issuecomment-1438674170
@HyukjinKwon @amaliujia can you please review?
If you think implementation of StorageLevel is not right I will close and can open a new one for the param only (when there's alternative implementation is available). The problem is you cant just add something to PySpark without touching Connect. I guess it's intentional.
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[GitHub] [spark] khalidmammadov closed pull request #40015: [SPARK-42437][PySpark][Connect] PySpark catalog.cacheTable will allow to specify storage level
Posted by "khalidmammadov (via GitHub)" <gi...@apache.org>.
khalidmammadov closed pull request #40015: [SPARK-42437][PySpark][Connect] PySpark catalog.cacheTable will allow to specify storage level
URL: https://github.com/apache/spark/pull/40015
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[GitHub] [spark] amaliujia commented on pull request #40015: [WIP][SPARK-42437][PySpark][Connect] PySpark catalog.cacheTable will allow to specify storage level
Posted by "amaliujia (via GitHub)" <gi...@apache.org>.
amaliujia commented on PR #40015:
URL: https://github.com/apache/spark/pull/40015#issuecomment-1431992781
cc @zhengruifeng IIRC there were some open questions to support storage level in Connect?
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[GitHub] [spark] zhengruifeng commented on a diff in pull request #40015: [SPARK-42437][PySpark][Connect] PySpark catalog.cacheTable will allow to specify storage level
Posted by "zhengruifeng (via GitHub)" <gi...@apache.org>.
zhengruifeng commented on code in PR #40015:
URL: https://github.com/apache/spark/pull/40015#discussion_r1119515771
##########
connector/connect/common/src/main/protobuf/spark/connect/types.proto:
##########
@@ -184,3 +184,15 @@ message DataType {
DataType sql_type = 5;
}
}
+
+enum StorageLevel {
Review Comment:
the problem is that the definitions are different between PySpark and SQL:
PySpark: `MEMORY_AND_DISK = useDisk=True, useMemory=True, useOffHeap=False, deserialized=False`
SQL: `MEMORY_AND_DISK = _useDisk=true, _useMemory=true, _useOffHeap=false, _deserialized=true`
also `MEMORY_AND_DISK_DESER ` was dedicated for PySpark, it is equivalent to `MEMORY_AND_DISK` in Scala side.
cc @cloud-fan @HyukjinKwon @amaliujia
also please follow [the guide](https://protobuf.dev/programming-guides/style/#enums) to define an `enum`, it should be like:
```
enum StorageLevel {
STORAGE_LEVEL_UNSPECIFIED = 0;
STORAGE_LEVEL_ DISK_ONLY = 1;
...
```
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[GitHub] [spark] ueshin commented on pull request #40015: [SPARK-42437][PYTHON][CONNECT] PySpark catalog.cacheTable will allow to specify storage level
Posted by "ueshin (via GitHub)" <gi...@apache.org>.
ueshin commented on PR #40015:
URL: https://github.com/apache/spark/pull/40015#issuecomment-1505864295
Thanks! merging to master.
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