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Posted to reviews@spark.apache.org by "Hisoka-X (via GitHub)" <gi...@apache.org> on 2023/04/11 13:48:56 UTC
[GitHub] [spark] Hisoka-X opened a new pull request, #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Hisoka-X opened a new pull request, #40741:
URL: https://github.com/apache/spark/pull/40741
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### What changes were proposed in this pull request?
1. add columns field on SQL/SQLCommand in connect protobuf to support send expression to server
2. parser columns in server to support sql with column
3. add string_formatter for connect module to support sql with dataframes.
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### Why are the changes needed?
To support sql with dataframes and columns in spark connect client.
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### Does this PR introduce _any_ user-facing change?
No
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### How was this patch tested?
Add new test
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[GitHub] [spark] HyukjinKwon commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1163806189
##########
python/pyspark/sql/connect/sql_formatter.py:
##########
@@ -0,0 +1,82 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import string
+import typing
+from typing import Any, Optional, List, Tuple, Sequence, Mapping
+import uuid
+
+from pyspark.sql.connect.proto import Expression
+
+if typing.TYPE_CHECKING:
+ from pyspark.sql.connect import SparkSession, DataFrame
+from pyspark.sql.connect.functions import lit
+
+
+class SQLStringFormatter(string.Formatter):
+ """
+ A standard ``string.Formatter`` in Python that can understand PySpark instances
+ with basic Python objects. This object has to be clear after the use for single SQL
+ query; cannot be reused across multiple SQL queries without cleaning.
+ """
+
+ def __init__(self, session: "SparkSession") -> None:
+ self._session: "SparkSession" = session
+ self._temp_views: List[Tuple[DataFrame, str]] = []
+ self._unresolvedColumns: typing.Dict[str, Expression] = {}
+
+ def get_field(self, field_name: str, args: Sequence[Any], kwargs: Mapping[str, Any]) -> Any:
+ obj, first = super(SQLStringFormatter, self).get_field(field_name, args, kwargs)
+ return self._convert_value(obj, field_name), first
+
+ def _convert_value(self, val: Any, field_name: str) -> Optional[str]:
+ """
+ Converts the given value into a SQL string.
+ """
+ from pyspark.sql.connect import Column, DataFrame
+
+ if isinstance(val, DataFrame):
+ for df, n in self._temp_views:
+ if df is val:
+ return n
+ df_name = "_pyspark_%s" % str(uuid.uuid4()).replace("-", "")
+ self._temp_views.append((val, df_name))
+ val.createOrReplaceTempView(df_name)
+ return df_name
+ if isinstance(val, Column):
+ for f, _ in self._unresolvedColumns.items():
+ if f is field_name:
+ break
+ self._unresolvedColumns[field_name] = val.expr.to_plan(self._session.client)
+ return wrap(field_name)
+ elif isinstance(val, str):
+ self._unresolvedColumns[field_name] = lit(val).expr.to_plan(self._session.client)
+ return wrap(field_name)
+ return val
+
+ def clear(self) -> None:
+ """TODO We need to find a better time to drop view"""
Review Comment:
can you try to `cache` and return the dataframe?
##########
python/pyspark/sql/connect/sql_formatter.py:
##########
@@ -0,0 +1,82 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import string
+import typing
+from typing import Any, Optional, List, Tuple, Sequence, Mapping
+import uuid
+
+from pyspark.sql.connect.proto import Expression
+
+if typing.TYPE_CHECKING:
+ from pyspark.sql.connect import SparkSession, DataFrame
+from pyspark.sql.connect.functions import lit
+
+
+class SQLStringFormatter(string.Formatter):
+ """
+ A standard ``string.Formatter`` in Python that can understand PySpark instances
+ with basic Python objects. This object has to be clear after the use for single SQL
+ query; cannot be reused across multiple SQL queries without cleaning.
+ """
+
+ def __init__(self, session: "SparkSession") -> None:
+ self._session: "SparkSession" = session
+ self._temp_views: List[Tuple[DataFrame, str]] = []
+ self._unresolvedColumns: typing.Dict[str, Expression] = {}
+
+ def get_field(self, field_name: str, args: Sequence[Any], kwargs: Mapping[str, Any]) -> Any:
+ obj, first = super(SQLStringFormatter, self).get_field(field_name, args, kwargs)
+ return self._convert_value(obj, field_name), first
+
+ def _convert_value(self, val: Any, field_name: str) -> Optional[str]:
+ """
+ Converts the given value into a SQL string.
+ """
+ from pyspark.sql.connect import Column, DataFrame
+
+ if isinstance(val, DataFrame):
+ for df, n in self._temp_views:
+ if df is val:
+ return n
+ df_name = "_pyspark_%s" % str(uuid.uuid4()).replace("-", "")
+ self._temp_views.append((val, df_name))
+ val.createOrReplaceTempView(df_name)
+ return df_name
+ if isinstance(val, Column):
+ for f, _ in self._unresolvedColumns.items():
+ if f is field_name:
+ break
+ self._unresolvedColumns[field_name] = val.expr.to_plan(self._session.client)
+ return wrap(field_name)
+ elif isinstance(val, str):
+ self._unresolvedColumns[field_name] = lit(val).expr.to_plan(self._session.client)
+ return wrap(field_name)
+ return val
+
+ def clear(self) -> None:
+ """TODO We need to find a better time to drop view"""
Review Comment:
can you try to `persist` and return the dataframe?
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[GitHub] [spark] HyukjinKwon commented on pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on PR #40741:
URL: https://github.com/apache/spark/pull/40741#issuecomment-1633955902
Sorry I completely forgot about this.
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[GitHub] [spark] Hisoka-X commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1163843165
##########
python/pyspark/sql/connect/sql_formatter.py:
##########
@@ -0,0 +1,82 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import string
+import typing
+from typing import Any, Optional, List, Tuple, Sequence, Mapping
+import uuid
+
+from pyspark.sql.connect.proto import Expression
+
+if typing.TYPE_CHECKING:
+ from pyspark.sql.connect import SparkSession, DataFrame
+from pyspark.sql.connect.functions import lit
+
+
+class SQLStringFormatter(string.Formatter):
+ """
+ A standard ``string.Formatter`` in Python that can understand PySpark instances
+ with basic Python objects. This object has to be clear after the use for single SQL
+ query; cannot be reused across multiple SQL queries without cleaning.
+ """
+
+ def __init__(self, session: "SparkSession") -> None:
+ self._session: "SparkSession" = session
+ self._temp_views: List[Tuple[DataFrame, str]] = []
+ self._unresolvedColumns: typing.Dict[str, Expression] = {}
+
+ def get_field(self, field_name: str, args: Sequence[Any], kwargs: Mapping[str, Any]) -> Any:
+ obj, first = super(SQLStringFormatter, self).get_field(field_name, args, kwargs)
+ return self._convert_value(obj, field_name), first
+
+ def _convert_value(self, val: Any, field_name: str) -> Optional[str]:
+ """
+ Converts the given value into a SQL string.
+ """
+ from pyspark.sql.connect import Column, DataFrame
+
+ if isinstance(val, DataFrame):
+ for df, n in self._temp_views:
+ if df is val:
+ return n
+ df_name = "_pyspark_%s" % str(uuid.uuid4()).replace("-", "")
+ self._temp_views.append((val, df_name))
+ val.createOrReplaceTempView(df_name)
+ return df_name
+ if isinstance(val, Column):
+ for f, _ in self._unresolvedColumns.items():
+ if f is field_name:
+ break
+ self._unresolvedColumns[field_name] = val.expr.to_plan(self._session.client)
+ return wrap(field_name)
+ elif isinstance(val, str):
+ self._unresolvedColumns[field_name] = lit(val).expr.to_plan(self._session.client)
+ return wrap(field_name)
+ return val
+
+ def clear(self) -> None:
+ """TODO We need to find a better time to drop view"""
Review Comment:
Not work, can't pass Analysis stage when use action.
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[GitHub] [spark] HyukjinKwon commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1163662948
##########
python/pyspark/sql/connect/sql_formatter.py:
##########
@@ -0,0 +1,82 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import string
+import typing
+from typing import Any, Optional, List, Tuple, Sequence, Mapping
+import uuid
+
+from pyspark.sql.connect.proto import Expression
+
+if typing.TYPE_CHECKING:
+ from pyspark.sql.connect import SparkSession, DataFrame
+from pyspark.sql.connect.functions import lit
+
+
+class SQLStringFormatter(string.Formatter):
+ """
+ A standard ``string.Formatter`` in Python that can understand PySpark instances
+ with basic Python objects. This object has to be clear after the use for single SQL
+ query; cannot be reused across multiple SQL queries without cleaning.
+ """
+
+ def __init__(self, session: "SparkSession") -> None:
+ self._session: "SparkSession" = session
+ self._temp_views: List[Tuple[DataFrame, str]] = []
+ self._unresolvedColumns: typing.Dict[str, Expression] = {}
+
+ def get_field(self, field_name: str, args: Sequence[Any], kwargs: Mapping[str, Any]) -> Any:
+ obj, first = super(SQLStringFormatter, self).get_field(field_name, args, kwargs)
+ return self._convert_value(obj, field_name), first
+
+ def _convert_value(self, val: Any, field_name: str) -> Optional[str]:
+ """
+ Converts the given value into a SQL string.
+ """
+ from pyspark.sql.connect import Column, DataFrame
+
+ if isinstance(val, DataFrame):
+ for df, n in self._temp_views:
+ if df is val:
+ return n
+ df_name = "_pyspark_%s" % str(uuid.uuid4()).replace("-", "")
+ self._temp_views.append((val, df_name))
+ val.createOrReplaceTempView(df_name)
+ return df_name
+ if isinstance(val, Column):
+ for f, _ in self._unresolvedColumns.items():
+ if f is field_name:
+ break
+ self._unresolvedColumns[field_name] = val.expr.to_plan(self._session.client)
+ return wrap(field_name)
+ elif isinstance(val, str):
+ self._unresolvedColumns[field_name] = lit(val).expr.to_plan(self._session.client)
+ return wrap(field_name)
+ return val
+
+ def clear(self) -> None:
+ """TODO We need to find a better time to drop view"""
Review Comment:
Hm, can't use just drop by the view by name? IIRC, Spark Connect's `sql` method itself eagerly executes the commands so the views should be created with `clear` is invoked.
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[GitHub] [spark] HyukjinKwon commented on pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on PR #40741:
URL: https://github.com/apache/spark/pull/40741#issuecomment-1633954741
Oh!
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[GitHub] [spark] Hisoka-X commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1162863680
##########
connector/connect/common/src/main/protobuf/spark/connect/commands.proto:
##########
@@ -57,6 +57,9 @@ message SqlCommand {
// (Optional) A map of parameter names to literal expressions.
map<string, Expression.Literal> args = 2;
+
+ // (Optional) A map of parameter names to column expressions.
+ map<string, Expression.UnresolvedAttribute> columns = 3;
Review Comment:
Add columns field, to support convert column to string on the server, to solve the problem connect client without jvm.
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[GitHub] [spark] Hisoka-X commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1164878200
##########
connector/connect/common/src/main/protobuf/spark/connect/relations.proto:
##########
@@ -111,6 +111,9 @@ message SQL {
// (Optional) A map of parameter names to literal expressions.
map<string, Expression.Literal> args = 2;
+
+ // (Optional) A map of parameter names to column expressions.
+ map<string, Expression.UnresolvedAttribute> columns = 3;
Review Comment:
It can also be merge together, but it doesn't look so clear on the interface.
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[GitHub] [spark] Hisoka-X commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1164155954
##########
python/pyspark/sql/connect/sql_formatter.py:
##########
@@ -0,0 +1,82 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import string
+import typing
+from typing import Any, Optional, List, Tuple, Sequence, Mapping
+import uuid
+
+from pyspark.sql.connect.proto import Expression
+
+if typing.TYPE_CHECKING:
+ from pyspark.sql.connect import SparkSession, DataFrame
+from pyspark.sql.connect.functions import lit
+
+
+class SQLStringFormatter(string.Formatter):
+ """
+ A standard ``string.Formatter`` in Python that can understand PySpark instances
+ with basic Python objects. This object has to be clear after the use for single SQL
+ query; cannot be reused across multiple SQL queries without cleaning.
+ """
+
+ def __init__(self, session: "SparkSession") -> None:
+ self._session: "SparkSession" = session
+ self._temp_views: List[Tuple[DataFrame, str]] = []
+ self._unresolvedColumns: typing.Dict[str, Expression] = {}
+
+ def get_field(self, field_name: str, args: Sequence[Any], kwargs: Mapping[str, Any]) -> Any:
+ obj, first = super(SQLStringFormatter, self).get_field(field_name, args, kwargs)
+ return self._convert_value(obj, field_name), first
+
+ def _convert_value(self, val: Any, field_name: str) -> Optional[str]:
+ """
+ Converts the given value into a SQL string.
+ """
+ from pyspark.sql.connect import Column, DataFrame
+
+ if isinstance(val, DataFrame):
+ for df, n in self._temp_views:
+ if df is val:
+ return n
+ df_name = "_pyspark_%s" % str(uuid.uuid4()).replace("-", "")
+ self._temp_views.append((val, df_name))
+ val.createOrReplaceTempView(df_name)
+ return df_name
+ if isinstance(val, Column):
+ for f, _ in self._unresolvedColumns.items():
+ if f is field_name:
+ break
+ self._unresolvedColumns[field_name] = val.expr.to_plan(self._session.client)
+ return wrap(field_name)
+ elif isinstance(val, str):
+ self._unresolvedColumns[field_name] = lit(val).expr.to_plan(self._session.client)
+ return wrap(field_name)
+ return val
+
+ def clear(self) -> None:
+ """TODO We need to find a better time to drop view"""
Review Comment:
Update: I try to extended `ParameterizedQuery` to add dataframes, but have one blocker is that parser does not recognize `{}` symbols. Extend parser will be a big change for other module. Can I remove support for dataframes in connect client sql temporary? @HyukjinKwon
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[GitHub] [spark] HyukjinKwon commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1163677911
##########
python/pyspark/sql/connect/sql_formatter.py:
##########
@@ -0,0 +1,82 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import string
+import typing
+from typing import Any, Optional, List, Tuple, Sequence, Mapping
+import uuid
+
+from pyspark.sql.connect.proto import Expression
+
+if typing.TYPE_CHECKING:
+ from pyspark.sql.connect import SparkSession, DataFrame
+from pyspark.sql.connect.functions import lit
+
+
+class SQLStringFormatter(string.Formatter):
+ """
+ A standard ``string.Formatter`` in Python that can understand PySpark instances
+ with basic Python objects. This object has to be clear after the use for single SQL
+ query; cannot be reused across multiple SQL queries without cleaning.
+ """
+
+ def __init__(self, session: "SparkSession") -> None:
+ self._session: "SparkSession" = session
+ self._temp_views: List[Tuple[DataFrame, str]] = []
+ self._unresolvedColumns: typing.Dict[str, Expression] = {}
+
+ def get_field(self, field_name: str, args: Sequence[Any], kwargs: Mapping[str, Any]) -> Any:
+ obj, first = super(SQLStringFormatter, self).get_field(field_name, args, kwargs)
+ return self._convert_value(obj, field_name), first
+
+ def _convert_value(self, val: Any, field_name: str) -> Optional[str]:
+ """
+ Converts the given value into a SQL string.
+ """
+ from pyspark.sql.connect import Column, DataFrame
+
+ if isinstance(val, DataFrame):
+ for df, n in self._temp_views:
+ if df is val:
+ return n
+ df_name = "_pyspark_%s" % str(uuid.uuid4()).replace("-", "")
+ self._temp_views.append((val, df_name))
+ val.createOrReplaceTempView(df_name)
+ return df_name
+ if isinstance(val, Column):
+ for f, _ in self._unresolvedColumns.items():
+ if f is field_name:
+ break
+ self._unresolvedColumns[field_name] = val.expr.to_plan(self._session.client)
+ return wrap(field_name)
+ elif isinstance(val, str):
+ self._unresolvedColumns[field_name] = lit(val).expr.to_plan(self._session.client)
+ return wrap(field_name)
+ return val
+
+ def clear(self) -> None:
+ """TODO We need to find a better time to drop view"""
Review Comment:
I think you can work around by calling `df.schema()` that triggers analysis for now, and commenting that this is a workaround to be fixed.
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[GitHub] [spark] Hisoka-X commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1163757517
##########
python/pyspark/sql/connect/session.py:
##########
@@ -395,13 +397,22 @@ def createDataFrame(
createDataFrame.__doc__ = PySparkSession.createDataFrame.__doc__
- def sql(self, sqlQuery: str, args: Optional[Dict[str, Any]] = None) -> "DataFrame":
- cmd = SQL(sqlQuery, args)
- data, properties = self.client.execute_command(cmd.command(self._client))
- if "sql_command_result" in properties:
- return DataFrame.withPlan(CachedRelation(properties["sql_command_result"]), self)
- else:
- return DataFrame.withPlan(SQL(sqlQuery, args), self)
+ def sql(
+ self, sqlQuery: str, args: Optional[Dict[str, Any]] = None, **kwargs: Any
+ ) -> "DataFrame":
+ formatter = SQLStringFormatter(self)
+ if len(kwargs) > 0:
+ sqlQuery = formatter.format(sqlQuery, **kwargs)
+ try:
+ cmd = SQL(sqlQuery, args, formatter.unresolvedColumns)
+ data, properties = self.client.execute_command(cmd.command(self._client))
+ if "sql_command_result" in properties:
+ return DataFrame.withPlan(CachedRelation(properties["sql_command_result"]), self)
+ else:
+ return DataFrame.withPlan(SQL(sqlQuery, args, formatter.unresolvedColumns), self)
Review Comment:
😂 It not work after tried, pyspark maybe worked because it will change plan after called. But connect will not change plan in dataframe (alway "SELECT" from 'ViewName')
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[GitHub] [spark] HyukjinKwon commented on pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on PR #40741:
URL: https://github.com/apache/spark/pull/40741#issuecomment-1506215271
cc @ueshin
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[GitHub] [spark] Hisoka-X commented on pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on PR #40741:
URL: https://github.com/apache/spark/pull/40741#issuecomment-1510595839
Hi guys, I want implement support sql with columns first, to avoid [sql with dataframes problem](https://github.com/apache/spark/pull/40741#discussion_r1163580352) before have better solution. If ok for you please let me know. Thanks.
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[GitHub] [spark] Hisoka-X commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1164870257
##########
connector/connect/common/src/main/protobuf/spark/connect/relations.proto:
##########
@@ -111,6 +111,9 @@ message SQL {
// (Optional) A map of parameter names to literal expressions.
map<string, Expression.Literal> args = 2;
+
+ // (Optional) A map of parameter names to column expressions.
+ map<string, Expression.UnresolvedAttribute> columns = 3;
Review Comment:
There are some different between args and columns. `SELECT {col} FROM t1 WHERE id=1` , the `{col}` used for `columns`. `SELECT id FROM t1 WHERE id= :value `, the `:value` used for `args`. The symbols used by the two are different, and the processing logic is also different. `{col}` is replaced before SQL analysis, and args is value replacement done in SQL analysis.
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[GitHub] [spark] amaliujia commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "amaliujia (via GitHub)" <gi...@apache.org>.
amaliujia commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1164416664
##########
connector/connect/common/src/main/protobuf/spark/connect/relations.proto:
##########
@@ -111,6 +111,9 @@ message SQL {
// (Optional) A map of parameter names to literal expressions.
map<string, Expression.Literal> args = 2;
+
+ // (Optional) A map of parameter names to column expressions.
+ map<string, Expression.UnresolvedAttribute> columns = 3;
Review Comment:
BTW I am not sure if it can pass proto breaking changes check but re-using proto fields could be a good idea. Maybe originally the type of `args` should already use `Expression`.
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[GitHub] [spark] Hisoka-X commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1163665874
##########
python/pyspark/sql/connect/sql_formatter.py:
##########
@@ -0,0 +1,82 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import string
+import typing
+from typing import Any, Optional, List, Tuple, Sequence, Mapping
+import uuid
+
+from pyspark.sql.connect.proto import Expression
+
+if typing.TYPE_CHECKING:
+ from pyspark.sql.connect import SparkSession, DataFrame
+from pyspark.sql.connect.functions import lit
+
+
+class SQLStringFormatter(string.Formatter):
+ """
+ A standard ``string.Formatter`` in Python that can understand PySpark instances
+ with basic Python objects. This object has to be clear after the use for single SQL
+ query; cannot be reused across multiple SQL queries without cleaning.
+ """
+
+ def __init__(self, session: "SparkSession") -> None:
+ self._session: "SparkSession" = session
+ self._temp_views: List[Tuple[DataFrame, str]] = []
+ self._unresolvedColumns: typing.Dict[str, Expression] = {}
+
+ def get_field(self, field_name: str, args: Sequence[Any], kwargs: Mapping[str, Any]) -> Any:
+ obj, first = super(SQLStringFormatter, self).get_field(field_name, args, kwargs)
+ return self._convert_value(obj, field_name), first
+
+ def _convert_value(self, val: Any, field_name: str) -> Optional[str]:
+ """
+ Converts the given value into a SQL string.
+ """
+ from pyspark.sql.connect import Column, DataFrame
+
+ if isinstance(val, DataFrame):
+ for df, n in self._temp_views:
+ if df is val:
+ return n
+ df_name = "_pyspark_%s" % str(uuid.uuid4()).replace("-", "")
+ self._temp_views.append((val, df_name))
+ val.createOrReplaceTempView(df_name)
+ return df_name
+ if isinstance(val, Column):
+ for f, _ in self._unresolvedColumns.items():
+ if f is field_name:
+ break
+ self._unresolvedColumns[field_name] = val.expr.to_plan(self._session.client)
+ return wrap(field_name)
+ elif isinstance(val, str):
+ self._unresolvedColumns[field_name] = lit(val).expr.to_plan(self._session.client)
+ return wrap(field_name)
+ return val
+
+ def clear(self) -> None:
+ """TODO We need to find a better time to drop view"""
Review Comment:
Eagerly executes not suit for SELECT query. If the sql are SELECT statement, clear view will cause VIEW_NOT_FOUND
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[GitHub] [spark] HyukjinKwon commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1163702110
##########
python/pyspark/sql/connect/session.py:
##########
@@ -395,13 +397,22 @@ def createDataFrame(
createDataFrame.__doc__ = PySparkSession.createDataFrame.__doc__
- def sql(self, sqlQuery: str, args: Optional[Dict[str, Any]] = None) -> "DataFrame":
- cmd = SQL(sqlQuery, args)
- data, properties = self.client.execute_command(cmd.command(self._client))
- if "sql_command_result" in properties:
- return DataFrame.withPlan(CachedRelation(properties["sql_command_result"]), self)
- else:
- return DataFrame.withPlan(SQL(sqlQuery, args), self)
+ def sql(
+ self, sqlQuery: str, args: Optional[Dict[str, Any]] = None, **kwargs: Any
+ ) -> "DataFrame":
+ formatter = SQLStringFormatter(self)
+ if len(kwargs) > 0:
+ sqlQuery = formatter.format(sqlQuery, **kwargs)
+ try:
+ cmd = SQL(sqlQuery, args, formatter.unresolvedColumns)
+ data, properties = self.client.execute_command(cmd.command(self._client))
+ if "sql_command_result" in properties:
+ return DataFrame.withPlan(CachedRelation(properties["sql_command_result"]), self)
+ else:
+ return DataFrame.withPlan(SQL(sqlQuery, args, formatter.unresolvedColumns), self)
Review Comment:
I meant sth like this
```python
if "sql_command_result" in properties:
ret = DataFrame.withPlan(CachedRelation(properties["sql_command_result"]), self)
else:
ret = DataFrame.withPlan(SQL(sqlQuery, args, formatter.unresolvedColumns), self)
if len(kwargs) > 0:
ret.schema # Workaround to drop view blah blah blah by trggering analysis. blah blah
return ret
```
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[GitHub] [spark] amaliujia commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "amaliujia (via GitHub)" <gi...@apache.org>.
amaliujia commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1164414092
##########
connector/connect/common/src/main/protobuf/spark/connect/relations.proto:
##########
@@ -111,6 +111,9 @@ message SQL {
// (Optional) A map of parameter names to literal expressions.
map<string, Expression.Literal> args = 2;
+
+ // (Optional) A map of parameter names to column expressions.
+ map<string, Expression.UnresolvedAttribute> columns = 3;
Review Comment:
I am wondering if we can merge `map<string, Expression.Literal> args = 2;` and `map<string, Expression.UnresolvedAttribute> columns = 3;` to `map<string, Expression>`?
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[GitHub] [spark] Hisoka-X commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1163757517
##########
python/pyspark/sql/connect/session.py:
##########
@@ -395,13 +397,22 @@ def createDataFrame(
createDataFrame.__doc__ = PySparkSession.createDataFrame.__doc__
- def sql(self, sqlQuery: str, args: Optional[Dict[str, Any]] = None) -> "DataFrame":
- cmd = SQL(sqlQuery, args)
- data, properties = self.client.execute_command(cmd.command(self._client))
- if "sql_command_result" in properties:
- return DataFrame.withPlan(CachedRelation(properties["sql_command_result"]), self)
- else:
- return DataFrame.withPlan(SQL(sqlQuery, args), self)
+ def sql(
+ self, sqlQuery: str, args: Optional[Dict[str, Any]] = None, **kwargs: Any
+ ) -> "DataFrame":
+ formatter = SQLStringFormatter(self)
+ if len(kwargs) > 0:
+ sqlQuery = formatter.format(sqlQuery, **kwargs)
+ try:
+ cmd = SQL(sqlQuery, args, formatter.unresolvedColumns)
+ data, properties = self.client.execute_command(cmd.command(self._client))
+ if "sql_command_result" in properties:
+ return DataFrame.withPlan(CachedRelation(properties["sql_command_result"]), self)
+ else:
+ return DataFrame.withPlan(SQL(sqlQuery, args, formatter.unresolvedColumns), self)
Review Comment:
😂 It not work after tried, pyspark maybe worked because it will change plan after called. But connect will not change plan in dataframe
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[GitHub] [spark] Hisoka-X commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1163580352
##########
python/pyspark/sql/connect/sql_formatter.py:
##########
@@ -0,0 +1,82 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import string
+import typing
+from typing import Any, Optional, List, Tuple, Sequence, Mapping
+import uuid
+
+from pyspark.sql.connect.proto import Expression
+
+if typing.TYPE_CHECKING:
+ from pyspark.sql.connect import SparkSession, DataFrame
+from pyspark.sql.connect.functions import lit
+
+
+class SQLStringFormatter(string.Formatter):
+ """
+ A standard ``string.Formatter`` in Python that can understand PySpark instances
+ with basic Python objects. This object has to be clear after the use for single SQL
+ query; cannot be reused across multiple SQL queries without cleaning.
+ """
+
+ def __init__(self, session: "SparkSession") -> None:
+ self._session: "SparkSession" = session
+ self._temp_views: List[Tuple[DataFrame, str]] = []
+ self._unresolvedColumns: typing.Dict[str, Expression] = {}
+
+ def get_field(self, field_name: str, args: Sequence[Any], kwargs: Mapping[str, Any]) -> Any:
+ obj, first = super(SQLStringFormatter, self).get_field(field_name, args, kwargs)
+ return self._convert_value(obj, field_name), first
+
+ def _convert_value(self, val: Any, field_name: str) -> Optional[str]:
+ """
+ Converts the given value into a SQL string.
+ """
+ from pyspark.sql.connect import Column, DataFrame
+
+ if isinstance(val, DataFrame):
+ for df, n in self._temp_views:
+ if df is val:
+ return n
+ df_name = "_pyspark_%s" % str(uuid.uuid4()).replace("-", "")
+ self._temp_views.append((val, df_name))
+ val.createOrReplaceTempView(df_name)
+ return df_name
+ if isinstance(val, Column):
+ for f, _ in self._unresolvedColumns.items():
+ if f is field_name:
+ break
+ self._unresolvedColumns[field_name] = val.expr.to_plan(self._session.client)
+ return wrap(field_name)
+ elif isinstance(val, str):
+ self._unresolvedColumns[field_name] = lit(val).expr.to_plan(self._session.client)
+ return wrap(field_name)
+ return val
+
+ def clear(self) -> None:
+ """TODO We need to find a better time to drop view"""
Review Comment:
There is something wrong with this version of the code
1. There is no way to drop view normally. Because the view is to pass the name into the sql for reference, not the logical plan of the reference, if the view is dropped before the action, the view cannot be processed normally. The difference between this and the original pyspark program is that the original pyspark saves the parsed logical plan, but now we save the name of the view. Connect has no way to save the parsed logical plan. If it does so, it will increase the complexity of the client side, because the original logical plan and the protobuf type plan must be maintained at the same time.
2. In order to solve this problem, `ParameterizedQuery` needs to be extended to support adding logical plans as parameters, just like the current `args`
@HyukjinKwon @cloud-fan @MaxGekk WDYT?
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[GitHub] [spark] Hisoka-X commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1163691632
##########
python/pyspark/sql/connect/sql_formatter.py:
##########
@@ -0,0 +1,82 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import string
+import typing
+from typing import Any, Optional, List, Tuple, Sequence, Mapping
+import uuid
+
+from pyspark.sql.connect.proto import Expression
+
+if typing.TYPE_CHECKING:
+ from pyspark.sql.connect import SparkSession, DataFrame
+from pyspark.sql.connect.functions import lit
+
+
+class SQLStringFormatter(string.Formatter):
+ """
+ A standard ``string.Formatter`` in Python that can understand PySpark instances
+ with basic Python objects. This object has to be clear after the use for single SQL
+ query; cannot be reused across multiple SQL queries without cleaning.
+ """
+
+ def __init__(self, session: "SparkSession") -> None:
+ self._session: "SparkSession" = session
+ self._temp_views: List[Tuple[DataFrame, str]] = []
+ self._unresolvedColumns: typing.Dict[str, Expression] = {}
+
+ def get_field(self, field_name: str, args: Sequence[Any], kwargs: Mapping[str, Any]) -> Any:
+ obj, first = super(SQLStringFormatter, self).get_field(field_name, args, kwargs)
+ return self._convert_value(obj, field_name), first
+
+ def _convert_value(self, val: Any, field_name: str) -> Optional[str]:
+ """
+ Converts the given value into a SQL string.
+ """
+ from pyspark.sql.connect import Column, DataFrame
+
+ if isinstance(val, DataFrame):
+ for df, n in self._temp_views:
+ if df is val:
+ return n
+ df_name = "_pyspark_%s" % str(uuid.uuid4()).replace("-", "")
+ self._temp_views.append((val, df_name))
+ val.createOrReplaceTempView(df_name)
+ return df_name
+ if isinstance(val, Column):
+ for f, _ in self._unresolvedColumns.items():
+ if f is field_name:
+ break
+ self._unresolvedColumns[field_name] = val.expr.to_plan(self._session.client)
+ return wrap(field_name)
+ elif isinstance(val, str):
+ self._unresolvedColumns[field_name] = lit(val).expr.to_plan(self._session.client)
+ return wrap(field_name)
+ return val
+
+ def clear(self) -> None:
+ """TODO We need to find a better time to drop view"""
Review Comment:
Sorry, I don't get the point. Where to call `df.schema()`? And the calling will resolved what problem? Like this?
<img width="401" alt="image" src="https://user-images.githubusercontent.com/32387433/231373441-75bb89a8-2c90-4ad0-9a4b-0cf60421dd86.png">
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[GitHub] [spark] Hisoka-X commented on pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on PR #40741:
URL: https://github.com/apache/spark/pull/40741#issuecomment-1633959938
@HyukjinKwon Never mind 😀. For me as long as the problem is solved, all is fine.
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[GitHub] [spark] Hisoka-X closed pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X closed pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
URL: https://github.com/apache/spark/pull/40741
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[GitHub] [spark] Hisoka-X commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1163665874
##########
python/pyspark/sql/connect/sql_formatter.py:
##########
@@ -0,0 +1,82 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import string
+import typing
+from typing import Any, Optional, List, Tuple, Sequence, Mapping
+import uuid
+
+from pyspark.sql.connect.proto import Expression
+
+if typing.TYPE_CHECKING:
+ from pyspark.sql.connect import SparkSession, DataFrame
+from pyspark.sql.connect.functions import lit
+
+
+class SQLStringFormatter(string.Formatter):
+ """
+ A standard ``string.Formatter`` in Python that can understand PySpark instances
+ with basic Python objects. This object has to be clear after the use for single SQL
+ query; cannot be reused across multiple SQL queries without cleaning.
+ """
+
+ def __init__(self, session: "SparkSession") -> None:
+ self._session: "SparkSession" = session
+ self._temp_views: List[Tuple[DataFrame, str]] = []
+ self._unresolvedColumns: typing.Dict[str, Expression] = {}
+
+ def get_field(self, field_name: str, args: Sequence[Any], kwargs: Mapping[str, Any]) -> Any:
+ obj, first = super(SQLStringFormatter, self).get_field(field_name, args, kwargs)
+ return self._convert_value(obj, field_name), first
+
+ def _convert_value(self, val: Any, field_name: str) -> Optional[str]:
+ """
+ Converts the given value into a SQL string.
+ """
+ from pyspark.sql.connect import Column, DataFrame
+
+ if isinstance(val, DataFrame):
+ for df, n in self._temp_views:
+ if df is val:
+ return n
+ df_name = "_pyspark_%s" % str(uuid.uuid4()).replace("-", "")
+ self._temp_views.append((val, df_name))
+ val.createOrReplaceTempView(df_name)
+ return df_name
+ if isinstance(val, Column):
+ for f, _ in self._unresolvedColumns.items():
+ if f is field_name:
+ break
+ self._unresolvedColumns[field_name] = val.expr.to_plan(self._session.client)
+ return wrap(field_name)
+ elif isinstance(val, str):
+ self._unresolvedColumns[field_name] = lit(val).expr.to_plan(self._session.client)
+ return wrap(field_name)
+ return val
+
+ def clear(self) -> None:
+ """TODO We need to find a better time to drop view"""
Review Comment:
Eagerly executes not suit for SELECT query. If the sql are SELECT statement, drop view will cause VIEW_NOT_FOUND
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[GitHub] [spark] amaliujia commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "amaliujia (via GitHub)" <gi...@apache.org>.
amaliujia commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1164414092
##########
connector/connect/common/src/main/protobuf/spark/connect/relations.proto:
##########
@@ -111,6 +111,9 @@ message SQL {
// (Optional) A map of parameter names to literal expressions.
map<string, Expression.Literal> args = 2;
+
+ // (Optional) A map of parameter names to column expressions.
+ map<string, Expression.UnresolvedAttribute> columns = 3;
Review Comment:
I am wondering if we can merge `map<string, Expression.Literal> args = 2;` and `map<string, Expression.UnresolvedAttribute> columns = 3;` to `map<string, Expressions> args = 2`?
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[GitHub] [spark] Hisoka-X commented on a diff in pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "Hisoka-X (via GitHub)" <gi...@apache.org>.
Hisoka-X commented on code in PR #40741:
URL: https://github.com/apache/spark/pull/40741#discussion_r1162860013
##########
python/pyspark/sql/tests/connect/test_connect_basic.py:
##########
@@ -2039,6 +2039,31 @@ def test_repr(self):
self.spark.sql(query).__repr__(),
)
+ def test_string_sql_formatter(self):
+ self.connect.sql(
+ "SELECT * FROM range(10) WHERE id > {bound1} AND id < {bound2}", bound1=7, bound2=9
+ ).show()
+
+ mydf = self.connect.range(10)
+ self.connect.sql(
+ "SELECT {col} FROM {mydf} WHERE id IN {x}", col=mydf.id, mydf=mydf, x=tuple(range(4))
+ ).show()
+
+ self.connect.sql(
Review Comment:
The test with dataframes can't passed on my env, I trying figure it out.
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[GitHub] [spark] HyukjinKwon commented on pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on PR #40741:
URL: https://github.com/apache/spark/pull/40741#issuecomment-1504449595
cc @MaxGekk
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[GitHub] [spark] HyukjinKwon commented on pull request #40741: [SPARK-41811][CONNECT][CLIENT] Support sql with dataframes and columns
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on PR #40741:
URL: https://github.com/apache/spark/pull/40741#issuecomment-1633954976
I totally forgot that we have an ongoing pr
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