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Posted to issues@paimon.apache.org by "leaves12138 (via GitHub)" <gi...@apache.org> on 2023/11/09 08:30:32 UTC
[PR] [spark] support spark sort compact procedure for unaware-bucket table [incubator-paimon]
leaves12138 opened a new pull request, #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296
### Purpose
Support spark sort procedure with order and zorder.
Usage :
CALL sort_compact('<database_name>.<table_name>', '<order/zorder>', '<column1>[,column2]...', ['<conditions>'])
example:
set spark.sql.shuffle.partitions=10;
CALL sort_compact('my_db.Orders1', 'zorder', 'f1,f2', 'f0=0');
conditions: "," means "AND" ";" means "OR"
If you want sort compact two partition date=01 and date=02, you need to write 'date=01;date=02'
If you want sort one partition with date=01 and day=01, you need to write 'date=01,day=01'
### Documentation
Wait to add
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Re: [PR] [spark] Introduce spark compact procedure [incubator-paimon]
Posted by "leaves12138 (via GitHub)" <gi...@apache.org>.
leaves12138 commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1393561499
##########
docs/content/engines/spark3.md:
##########
@@ -425,6 +425,29 @@ val query = spark.readStream
*/
```
+## Spark Procedure
+
+This section introduce all available spark procedures about paimon.
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 4%">Procedure Name</th>
+ <th class="text-left" style="width: 4%">Usage</th>
+ <th class="text-left" style="width: 20%">Explaination</th>
+ <th class="text-left" style="width: 4%">Example</th>
+ </tr>
+ </thead>
+ <tbody style="font-size: 12px; ">
+ <tr>
+ <td>compact</td>
+ <td><nobr>CALL compact('<identifier>','<partitions>','<sort_type>','<columns>')</nobr><br>CALL compact(table => '<identifier>' [,partitions => '<partitions>'] [, order_strategy =>'<sort_type>'] [,order_by => '<columns>'])</td>
+ <td>identifier: the target table identifier<br><br><nobr>partitions: partition filter<br> "," means "AND"<br>";" means "OR"</nobr><br><br>order_strategy: 'order' or 'zorder' or 'none' <br><br><nobr>order_columns: the columns need to be sort</nobr><br><br>If you want sort compact two partitions date=01 and date=02, you need to write 'date=01;date=02'<br><br>If you want sort one partition with date=01 and day=01, you need to write 'date=01,day=01'</td>
+ <td><nobr>SET spark.sql.shuffle.partitions=10; --set the sort parallelism</nobr> <nobr>CALL paimon.sys.compact('my_db.Orders1','f0=0,f1=1;f0=1,f1=1', 'zorder', 'f1,f2');</nobr><br><nobr>CALL paimon.sys.compact(table => 'T', partitions => 'p=0', order_strategy => 'zorder', order_by => 'a,b')</nobr></td>
Review Comment:
We just support this kind like iceberg, we don't recomment to use this. User could determine what he like.
##########
docs/content/engines/spark3.md:
##########
@@ -425,6 +425,29 @@ val query = spark.readStream
*/
```
+## Spark Procedure
+
+This section introduce all available spark procedures about paimon.
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 4%">Procedure Name</th>
+ <th class="text-left" style="width: 4%">Usage</th>
+ <th class="text-left" style="width: 20%">Explaination</th>
+ <th class="text-left" style="width: 4%">Example</th>
+ </tr>
+ </thead>
+ <tbody style="font-size: 12px; ">
+ <tr>
+ <td>compact</td>
+ <td><nobr>CALL compact('<identifier>','<partitions>','<sort_type>','<columns>')</nobr><br>CALL compact(table => '<identifier>' [,partitions => '<partitions>'] [, order_strategy =>'<sort_type>'] [,order_by => '<columns>'])</td>
+ <td>identifier: the target table identifier<br><br><nobr>partitions: partition filter<br> "," means "AND"<br>";" means "OR"</nobr><br><br>order_strategy: 'order' or 'zorder' or 'none' <br><br><nobr>order_columns: the columns need to be sort</nobr><br><br>If you want sort compact two partitions date=01 and date=02, you need to write 'date=01;date=02'<br><br>If you want sort one partition with date=01 and day=01, you need to write 'date=01,day=01'</td>
+ <td><nobr>SET spark.sql.shuffle.partitions=10; --set the sort parallelism</nobr> <nobr>CALL paimon.sys.compact('my_db.Orders1','f0=0,f1=1;f0=1,f1=1', 'zorder', 'f1,f2');</nobr><br><nobr>CALL paimon.sys.compact(table => 'T', partitions => 'p=0', order_strategy => 'zorder', order_by => 'a,b')</nobr></td>
Review Comment:
> Here we may need to remind that "paimon" is the customized catalog name, or just use sys.xxx under paimon catalog namespace
Fixed this.
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Re: [PR] [spark] Introduce spark compact procedure [incubator-paimon]
Posted by "JingsongLi (via GitHub)" <gi...@apache.org>.
JingsongLi commented on PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#issuecomment-1808185917
CC @Zouxxyy to review again~
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Re: [PR] [spark] Introduce spark compact procedure [incubator-paimon]
Posted by "leaves12138 (via GitHub)" <gi...@apache.org>.
leaves12138 commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1393565761
##########
paimon-spark/paimon-spark-3.4/src/test/scala/org/apache/paimon/spark/sql/CreateAndDeleteTagProcedureTest.scala:
##########
@@ -68,13 +68,14 @@ class CreateAndDeleteTagProcedureTest extends PaimonSparkTestBase with StreamTes
stream.processAllAvailable()
checkAnswer(query(), Row(1, "a") :: Row(2, "b2") :: Nil)
checkAnswer(
- spark.sql("CALL create_tag(table => 'test.T', tag => 'test_tag', snapshot => 2)"),
+ spark.sql(
+ "CALL paimon.sys.create_tag(table => 'test.T', tag => 'test_tag', snapshot => 2)"),
Review Comment:
Tagged in docs
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Re: [PR] [spark] Introduce spark sort compact procedure for unaware-bucket table [incubator-paimon]
Posted by "Zouxxyy (via GitHub)" <gi...@apache.org>.
Zouxxyy commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1388107790
##########
paimon-spark/paimon-spark-common/src/main/java/org/apache/paimon/spark/procedure/SortCompactProcedure.java:
##########
@@ -0,0 +1,164 @@
+/*
+ * 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.
+ */
+
+package org.apache.paimon.spark.procedure;
+
+import org.apache.paimon.CoreOptions;
+import org.apache.paimon.annotation.VisibleForTesting;
+import org.apache.paimon.options.Options;
+import org.apache.paimon.spark.SaveMode;
+import org.apache.paimon.spark.commands.WriteIntoPaimonTable;
+import org.apache.paimon.spark.sort.TableSorter;
+import org.apache.paimon.table.AppendOnlyFileStoreTable;
+import org.apache.paimon.table.FileStoreTable;
+import org.apache.paimon.utils.ParameterUtils;
+import org.apache.paimon.utils.Preconditions;
+import org.apache.paimon.utils.StringUtils;
+
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.connector.catalog.Identifier;
+import org.apache.spark.sql.connector.catalog.TableCatalog;
+import org.apache.spark.sql.types.DataTypes;
+import org.apache.spark.sql.types.Metadata;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+
+import javax.annotation.Nullable;
+
+import java.util.Arrays;
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
+
+import static org.apache.spark.sql.types.DataTypes.StringType;
+
+/** Sort compact procedure for sort unaware-bucket table. */
+public class SortCompactProcedure extends BaseProcedure {
+
+ private static final ProcedureParameter[] PARAMETERS =
+ new ProcedureParameter[] {
+ ProcedureParameter.required("table", StringType),
+ ProcedureParameter.required("order_type", StringType),
+ ProcedureParameter.required("columns", StringType),
+ ProcedureParameter.optional("conditions", StringType),
+ };
+
+ private static final StructType OUTPUT_TYPE =
+ new StructType(
+ new StructField[] {
+ new StructField("result", DataTypes.BooleanType, true, Metadata.empty())
+ });
+
+ protected SortCompactProcedure(TableCatalog tableCatalog) {
+ super(tableCatalog);
+ }
+
+ @Override
+ public ProcedureParameter[] parameters() {
+ return PARAMETERS;
+ }
+
+ @Override
+ public StructType outputType() {
+ return OUTPUT_TYPE;
+ }
+
+ @Override
+ public InternalRow[] call(InternalRow args) {
+ Preconditions.checkArgument(args.numFields() >= 3);
+ Identifier tableIdent = toIdentifier(args.getString(0), PARAMETERS[0].name());
+ String sortType = args.getString(1);
+ List<String> sortColumns = Arrays.asList(args.getString(2).split(","));
+
+ String partitionFilter = args.isNullAt(3) ? null : toWhere(args.getString(3));
+
+ return modifyPaimonTable(
+ tableIdent,
+ table -> {
+ Preconditions.checkArgument(table instanceof FileStoreTable);
+ InternalRow internalRow =
+ newInternalRow(
+ execute(
+ (FileStoreTable) table,
+ sortType,
+ sortColumns,
+ partitionFilter));
+ return new InternalRow[] {internalRow};
+ });
+ }
+
+ @Override
+ public String description() {
+ return "This procedure execute sort compact action on unaware-bucket table.";
+ }
+
+ private boolean execute(
+ FileStoreTable table,
+ String sortType,
+ List<String> sortColumns,
+ @Nullable String filter) {
+ CoreOptions coreOptions = table.store().options();
+
+ if (!(table instanceof AppendOnlyFileStoreTable) || coreOptions.bucket() != -1) {
+ throw new UnsupportedOperationException(
+ "Spark sort compact only support unaware-bucket append-only table yet.");
+ }
+
+ Dataset<Row> row = spark().read().format("paimon").load(coreOptions.path().getPath());
+ row = StringUtils.isBlank(filter) ? row : row.where(filter);
+ new WriteIntoPaimonTable(
+ table,
+ SaveMode.dynamic(),
+ TableSorter.getSorter(table, sortType, sortColumns).sort(row),
+ new Options())
+ .run(spark());
+ return true;
+ }
+
+ @VisibleForTesting
+ static String toWhere(String partitions) {
+ if (StringUtils.isBlank(partitions)) {
+ return null;
+ }
+
+ List<Map<String, String>> maps = ParameterUtils.getPartitions(partitions.split(";"));
+
+ return maps.stream()
Review Comment:
We can directly pass a where condition string (such as p1 = a and p2 > b) and then let spark analyze it by itself.
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Re: [PR] [spark] Introduce spark compact procedure [incubator-paimon]
Posted by "Zouxxyy (via GitHub)" <gi...@apache.org>.
Zouxxyy commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1392119659
##########
paimon-spark/paimon-spark-3.4/src/test/scala/org/apache/paimon/spark/sql/CreateAndDeleteTagProcedureTest.scala:
##########
@@ -68,13 +68,14 @@ class CreateAndDeleteTagProcedureTest extends PaimonSparkTestBase with StreamTes
stream.processAllAvailable()
checkAnswer(query(), Row(1, "a") :: Row(2, "b2") :: Nil)
checkAnswer(
- spark.sql("CALL create_tag(table => 'test.T', tag => 'test_tag', snapshot => 2)"),
+ spark.sql(
+ "CALL paimon.sys.create_tag(table => 'test.T', tag => 'test_tag', snapshot => 2)"),
Review Comment:
here we can just use sys.create_tag
##########
docs/content/engines/spark3.md:
##########
@@ -425,6 +425,29 @@ val query = spark.readStream
*/
```
+## Spark Procedure
+
+This section introduce all available spark procedures about paimon.
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 4%">Procedure Name</th>
+ <th class="text-left" style="width: 4%">Usage</th>
+ <th class="text-left" style="width: 20%">Explaination</th>
+ <th class="text-left" style="width: 4%">Example</th>
+ </tr>
+ </thead>
+ <tbody style="font-size: 12px; ">
+ <tr>
+ <td>compact</td>
+ <td><nobr>CALL compact('<identifier>','<partitions>','<sort_type>','<columns>')</nobr><br>CALL compact(table => '<identifier>' [,partitions => '<partitions>'] [, order_strategy =>'<sort_type>'] [,order_by => '<columns>'])</td>
+ <td>identifier: the target table identifier<br><br><nobr>partitions: partition filter<br> "," means "AND"<br>";" means "OR"</nobr><br><br>order_strategy: 'order' or 'zorder' or 'none' <br><br><nobr>order_columns: the columns need to be sort</nobr><br><br>If you want sort compact two partitions date=01 and date=02, you need to write 'date=01;date=02'<br><br>If you want sort one partition with date=01 and day=01, you need to write 'date=01,day=01'</td>
+ <td><nobr>SET spark.sql.shuffle.partitions=10; --set the sort parallelism</nobr> <nobr>CALL paimon.sys.compact('my_db.Orders1','f0=0,f1=1;f0=1,f1=1', 'zorder', 'f1,f2');</nobr><br><nobr>CALL paimon.sys.compact(table => 'T', partitions => 'p=0', order_strategy => 'zorder', order_by => 'a,b')</nobr></td>
Review Comment:
I don't think omitting parameter name is a good way to use procedures, it's not clear enough. Although flink currently does not support (parameterName => value) ?
##########
docs/content/engines/spark3.md:
##########
@@ -425,6 +425,29 @@ val query = spark.readStream
*/
```
+## Spark Procedure
+
+This section introduce all available spark procedures about paimon.
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 4%">Procedure Name</th>
+ <th class="text-left" style="width: 4%">Usage</th>
+ <th class="text-left" style="width: 20%">Explaination</th>
+ <th class="text-left" style="width: 4%">Example</th>
+ </tr>
+ </thead>
+ <tbody style="font-size: 12px; ">
+ <tr>
+ <td>compact</td>
+ <td><nobr>CALL compact('<identifier>','<partitions>','<sort_type>','<columns>')</nobr><br>CALL compact(table => '<identifier>' [,partitions => '<partitions>'] [, order_strategy =>'<sort_type>'] [,order_by => '<columns>'])</td>
+ <td>identifier: the target table identifier<br><br><nobr>partitions: partition filter<br> "," means "AND"<br>";" means "OR"</nobr><br><br>order_strategy: 'order' or 'zorder' or 'none' <br><br><nobr>order_columns: the columns need to be sort</nobr><br><br>If you want sort compact two partitions date=01 and date=02, you need to write 'date=01;date=02'<br><br>If you want sort one partition with date=01 and day=01, you need to write 'date=01,day=01'</td>
Review Comment:
Need to explain what the default behavior of optional parameter
##########
docs/content/engines/spark3.md:
##########
@@ -425,6 +425,29 @@ val query = spark.readStream
*/
```
+## Spark Procedure
+
+This section introduce all available spark procedures about paimon.
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 4%">Procedure Name</th>
+ <th class="text-left" style="width: 4%">Usage</th>
+ <th class="text-left" style="width: 20%">Explaination</th>
+ <th class="text-left" style="width: 4%">Example</th>
+ </tr>
+ </thead>
+ <tbody style="font-size: 12px; ">
+ <tr>
+ <td>compact</td>
+ <td><nobr>CALL compact('<identifier>','<partitions>','<sort_type>','<columns>')</nobr><br>CALL compact(table => '<identifier>' [,partitions => '<partitions>'] [, order_strategy =>'<sort_type>'] [,order_by => '<columns>'])</td>
+ <td>identifier: the target table identifier<br><br><nobr>partitions: partition filter<br> "," means "AND"<br>";" means "OR"</nobr><br><br>order_strategy: 'order' or 'zorder' or 'none' <br><br><nobr>order_columns: the columns need to be sort</nobr><br><br>If you want sort compact two partitions date=01 and date=02, you need to write 'date=01;date=02'<br><br>If you want sort one partition with date=01 and day=01, you need to write 'date=01,day=01'</td>
+ <td><nobr>SET spark.sql.shuffle.partitions=10; --set the sort parallelism</nobr> <nobr>CALL paimon.sys.compact('my_db.Orders1','f0=0,f1=1;f0=1,f1=1', 'zorder', 'f1,f2');</nobr><br><nobr>CALL paimon.sys.compact(table => 'T', partitions => 'p=0', order_strategy => 'zorder', order_by => 'a,b')</nobr></td>
Review Comment:
Here we may need to remind that "paimon" is the customized catalog name, or just use sys.xxx under paimon catalog namespace
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Re: [PR] [spark] Introduce spark compact procedure [incubator-paimon]
Posted by "Zouxxyy (via GitHub)" <gi...@apache.org>.
Zouxxyy commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1392125881
##########
docs/content/engines/spark3.md:
##########
@@ -425,6 +425,29 @@ val query = spark.readStream
*/
```
+## Spark Procedure
+
+This section introduce all available spark procedures about paimon.
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 4%">Procedure Name</th>
+ <th class="text-left" style="width: 4%">Usage</th>
+ <th class="text-left" style="width: 20%">Explaination</th>
+ <th class="text-left" style="width: 4%">Example</th>
+ </tr>
+ </thead>
+ <tbody style="font-size: 12px; ">
+ <tr>
+ <td>compact</td>
+ <td><nobr>CALL compact('<identifier>','<partitions>','<sort_type>','<columns>')</nobr><br>CALL compact(table => '<identifier>' [,partitions => '<partitions>'] [, order_strategy =>'<sort_type>'] [,order_by => '<columns>'])</td>
+ <td>identifier: the target table identifier<br><br><nobr>partitions: partition filter<br> "," means "AND"<br>";" means "OR"</nobr><br><br>order_strategy: 'order' or 'zorder' or 'none' <br><br><nobr>order_columns: the columns need to be sort</nobr><br><br>If you want sort compact two partitions date=01 and date=02, you need to write 'date=01;date=02'<br><br>If you want sort one partition with date=01 and day=01, you need to write 'date=01,day=01'</td>
+ <td><nobr>SET spark.sql.shuffle.partitions=10; --set the sort parallelism</nobr> <nobr>CALL paimon.sys.compact('my_db.Orders1','f0=0,f1=1;f0=1,f1=1', 'zorder', 'f1,f2');</nobr><br><nobr>CALL paimon.sys.compact(table => 'T', partitions => 'p=0', order_strategy => 'zorder', order_by => 'a,b')</nobr></td>
Review Comment:
I don't think omitting parameter name is a good way to use procedures, it's not clear enough and does not support order swapping. Although flink currently does not support (parameterName => value) ?
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Re: [PR] [spark] Introduce spark compact procedure [incubator-paimon]
Posted by "Zouxxyy (via GitHub)" <gi...@apache.org>.
Zouxxyy commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1392118326
##########
docs/content/engines/spark3.md:
##########
@@ -425,6 +425,29 @@ val query = spark.readStream
*/
```
+## Spark Procedure
+
+This section introduce all available spark procedures about paimon.
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 4%">Procedure Name</th>
+ <th class="text-left" style="width: 4%">Usage</th>
+ <th class="text-left" style="width: 20%">Explaination</th>
+ <th class="text-left" style="width: 4%">Example</th>
+ </tr>
+ </thead>
+ <tbody style="font-size: 12px; ">
+ <tr>
+ <td>compact</td>
+ <td><nobr>CALL compact('<identifier>','<partitions>','<sort_type>','<columns>')</nobr><br>CALL compact(table => '<identifier>' [,partitions => '<partitions>'] [, order_strategy =>'<sort_type>'] [,order_by => '<columns>'])</td>
+ <td>identifier: the target table identifier<br><br><nobr>partitions: partition filter<br> "," means "AND"<br>";" means "OR"</nobr><br><br>order_strategy: 'order' or 'zorder' or 'none' <br><br><nobr>order_columns: the columns need to be sort</nobr><br><br>If you want sort compact two partitions date=01 and date=02, you need to write 'date=01;date=02'<br><br>If you want sort one partition with date=01 and day=01, you need to write 'date=01,day=01'</td>
+ <td><nobr>SET spark.sql.shuffle.partitions=10; --set the sort parallelism</nobr> <nobr>CALL paimon.sys.compact('my_db.Orders1','f0=0,f1=1;f0=1,f1=1', 'zorder', 'f1,f2');</nobr><br><nobr>CALL paimon.sys.compact(table => 'T', partitions => 'p=0', order_strategy => 'zorder', order_by => 'a,b')</nobr></td>
Review Comment:
Here we may need to remind that "paimon" is the customized catalog name, or just use sys.xxx under paimon catalog namespace
##########
docs/content/engines/spark3.md:
##########
@@ -425,6 +425,29 @@ val query = spark.readStream
*/
```
+## Spark Procedure
+
+This section introduce all available spark procedures about paimon.
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 4%">Procedure Name</th>
+ <th class="text-left" style="width: 4%">Usage</th>
+ <th class="text-left" style="width: 20%">Explaination</th>
+ <th class="text-left" style="width: 4%">Example</th>
+ </tr>
+ </thead>
+ <tbody style="font-size: 12px; ">
+ <tr>
+ <td>compact</td>
+ <td><nobr>CALL compact('<identifier>','<partitions>','<sort_type>','<columns>')</nobr><br>CALL compact(table => '<identifier>' [,partitions => '<partitions>'] [, order_strategy =>'<sort_type>'] [,order_by => '<columns>'])</td>
+ <td>identifier: the target table identifier<br><br><nobr>partitions: partition filter<br> "," means "AND"<br>";" means "OR"</nobr><br><br>order_strategy: 'order' or 'zorder' or 'none' <br><br><nobr>order_columns: the columns need to be sort</nobr><br><br>If you want sort compact two partitions date=01 and date=02, you need to write 'date=01;date=02'<br><br>If you want sort one partition with date=01 and day=01, you need to write 'date=01,day=01'</td>
+ <td><nobr>SET spark.sql.shuffle.partitions=10; --set the sort parallelism</nobr> <nobr>CALL paimon.sys.compact('my_db.Orders1','f0=0,f1=1;f0=1,f1=1', 'zorder', 'f1,f2');</nobr><br><nobr>CALL paimon.sys.compact(table => 'T', partitions => 'p=0', order_strategy => 'zorder', order_by => 'a,b')</nobr></td>
Review Comment:
Here we may need to remind that "paimon" is the customized catalog name, or just use sys.xxx under paimon catalog namespace
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Re: [PR] [spark] Introduce spark sort compact procedure for unaware-bucket table [incubator-paimon]
Posted by "leaves12138 (via GitHub)" <gi...@apache.org>.
leaves12138 commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1388837880
##########
paimon-spark/paimon-spark-common/src/main/java/org/apache/paimon/spark/procedure/SortCompactProcedure.java:
##########
@@ -0,0 +1,164 @@
+/*
+ * 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.
+ */
+
+package org.apache.paimon.spark.procedure;
+
+import org.apache.paimon.CoreOptions;
+import org.apache.paimon.annotation.VisibleForTesting;
+import org.apache.paimon.options.Options;
+import org.apache.paimon.spark.SaveMode;
+import org.apache.paimon.spark.commands.WriteIntoPaimonTable;
+import org.apache.paimon.spark.sort.TableSorter;
+import org.apache.paimon.table.AppendOnlyFileStoreTable;
+import org.apache.paimon.table.FileStoreTable;
+import org.apache.paimon.utils.ParameterUtils;
+import org.apache.paimon.utils.Preconditions;
+import org.apache.paimon.utils.StringUtils;
+
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.connector.catalog.Identifier;
+import org.apache.spark.sql.connector.catalog.TableCatalog;
+import org.apache.spark.sql.types.DataTypes;
+import org.apache.spark.sql.types.Metadata;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+
+import javax.annotation.Nullable;
+
+import java.util.Arrays;
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
+
+import static org.apache.spark.sql.types.DataTypes.StringType;
+
+/** Sort compact procedure for sort unaware-bucket table. */
+public class SortCompactProcedure extends BaseProcedure {
+
+ private static final ProcedureParameter[] PARAMETERS =
+ new ProcedureParameter[] {
+ ProcedureParameter.required("table", StringType),
+ ProcedureParameter.required("order_type", StringType),
+ ProcedureParameter.required("columns", StringType),
+ ProcedureParameter.optional("conditions", StringType),
+ };
+
+ private static final StructType OUTPUT_TYPE =
+ new StructType(
+ new StructField[] {
+ new StructField("result", DataTypes.BooleanType, true, Metadata.empty())
+ });
+
+ protected SortCompactProcedure(TableCatalog tableCatalog) {
+ super(tableCatalog);
+ }
+
+ @Override
+ public ProcedureParameter[] parameters() {
+ return PARAMETERS;
+ }
+
+ @Override
+ public StructType outputType() {
+ return OUTPUT_TYPE;
+ }
+
+ @Override
+ public InternalRow[] call(InternalRow args) {
+ Preconditions.checkArgument(args.numFields() >= 3);
+ Identifier tableIdent = toIdentifier(args.getString(0), PARAMETERS[0].name());
+ String sortType = args.getString(1);
+ List<String> sortColumns = Arrays.asList(args.getString(2).split(","));
+
+ String partitionFilter = args.isNullAt(3) ? null : toWhere(args.getString(3));
+
+ return modifyPaimonTable(
+ tableIdent,
+ table -> {
+ Preconditions.checkArgument(table instanceof FileStoreTable);
+ InternalRow internalRow =
+ newInternalRow(
+ execute(
+ (FileStoreTable) table,
+ sortType,
+ sortColumns,
+ partitionFilter));
+ return new InternalRow[] {internalRow};
+ });
+ }
+
+ @Override
+ public String description() {
+ return "This procedure execute sort compact action on unaware-bucket table.";
+ }
+
+ private boolean execute(
+ FileStoreTable table,
+ String sortType,
+ List<String> sortColumns,
+ @Nullable String filter) {
+ CoreOptions coreOptions = table.store().options();
+
+ if (!(table instanceof AppendOnlyFileStoreTable) || coreOptions.bucket() != -1) {
+ throw new UnsupportedOperationException(
+ "Spark sort compact only support unaware-bucket append-only table yet.");
+ }
+
+ Dataset<Row> row = spark().read().format("paimon").load(coreOptions.path().getPath());
+ row = StringUtils.isBlank(filter) ? row : row.where(filter);
+ new WriteIntoPaimonTable(
+ table,
+ SaveMode.dynamic(),
+ TableSorter.getSorter(table, sortType, sortColumns).sort(row),
+ new Options())
+ .run(spark());
+ return true;
+ }
+
+ @VisibleForTesting
+ static String toWhere(String partitions) {
+ if (StringUtils.isBlank(partitions)) {
+ return null;
+ }
+
+ List<Map<String, String>> maps = ParameterUtils.getPartitions(partitions.split(";"));
+
+ return maps.stream()
Review Comment:
For compatible with flink action, but iceberg does like what you say.
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Re: [PR] [spark] Introduce spark compact procedure [incubator-paimon]
Posted by "leaves12138 (via GitHub)" <gi...@apache.org>.
leaves12138 commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1393562178
##########
docs/content/engines/spark3.md:
##########
@@ -425,6 +425,29 @@ val query = spark.readStream
*/
```
+## Spark Procedure
+
+This section introduce all available spark procedures about paimon.
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 4%">Procedure Name</th>
+ <th class="text-left" style="width: 4%">Usage</th>
+ <th class="text-left" style="width: 20%">Explaination</th>
+ <th class="text-left" style="width: 4%">Example</th>
+ </tr>
+ </thead>
+ <tbody style="font-size: 12px; ">
+ <tr>
+ <td>compact</td>
+ <td><nobr>CALL compact('<identifier>','<partitions>','<sort_type>','<columns>')</nobr><br>CALL compact(table => '<identifier>' [,partitions => '<partitions>'] [, order_strategy =>'<sort_type>'] [,order_by => '<columns>'])</td>
+ <td>identifier: the target table identifier<br><br><nobr>partitions: partition filter<br> "," means "AND"<br>";" means "OR"</nobr><br><br>order_strategy: 'order' or 'zorder' or 'none' <br><br><nobr>order_columns: the columns need to be sort</nobr><br><br>If you want sort compact two partitions date=01 and date=02, you need to write 'date=01;date=02'<br><br>If you want sort one partition with date=01 and day=01, you need to write 'date=01,day=01'</td>
Review Comment:
Fixed this.
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Re: [PR] [spark] Introduce spark sort compact procedure for unaware-bucket table [incubator-paimon]
Posted by "leaves12138 (via GitHub)" <gi...@apache.org>.
leaves12138 commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1388837880
##########
paimon-spark/paimon-spark-common/src/main/java/org/apache/paimon/spark/procedure/SortCompactProcedure.java:
##########
@@ -0,0 +1,164 @@
+/*
+ * 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.
+ */
+
+package org.apache.paimon.spark.procedure;
+
+import org.apache.paimon.CoreOptions;
+import org.apache.paimon.annotation.VisibleForTesting;
+import org.apache.paimon.options.Options;
+import org.apache.paimon.spark.SaveMode;
+import org.apache.paimon.spark.commands.WriteIntoPaimonTable;
+import org.apache.paimon.spark.sort.TableSorter;
+import org.apache.paimon.table.AppendOnlyFileStoreTable;
+import org.apache.paimon.table.FileStoreTable;
+import org.apache.paimon.utils.ParameterUtils;
+import org.apache.paimon.utils.Preconditions;
+import org.apache.paimon.utils.StringUtils;
+
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.connector.catalog.Identifier;
+import org.apache.spark.sql.connector.catalog.TableCatalog;
+import org.apache.spark.sql.types.DataTypes;
+import org.apache.spark.sql.types.Metadata;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+
+import javax.annotation.Nullable;
+
+import java.util.Arrays;
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
+
+import static org.apache.spark.sql.types.DataTypes.StringType;
+
+/** Sort compact procedure for sort unaware-bucket table. */
+public class SortCompactProcedure extends BaseProcedure {
+
+ private static final ProcedureParameter[] PARAMETERS =
+ new ProcedureParameter[] {
+ ProcedureParameter.required("table", StringType),
+ ProcedureParameter.required("order_type", StringType),
+ ProcedureParameter.required("columns", StringType),
+ ProcedureParameter.optional("conditions", StringType),
+ };
+
+ private static final StructType OUTPUT_TYPE =
+ new StructType(
+ new StructField[] {
+ new StructField("result", DataTypes.BooleanType, true, Metadata.empty())
+ });
+
+ protected SortCompactProcedure(TableCatalog tableCatalog) {
+ super(tableCatalog);
+ }
+
+ @Override
+ public ProcedureParameter[] parameters() {
+ return PARAMETERS;
+ }
+
+ @Override
+ public StructType outputType() {
+ return OUTPUT_TYPE;
+ }
+
+ @Override
+ public InternalRow[] call(InternalRow args) {
+ Preconditions.checkArgument(args.numFields() >= 3);
+ Identifier tableIdent = toIdentifier(args.getString(0), PARAMETERS[0].name());
+ String sortType = args.getString(1);
+ List<String> sortColumns = Arrays.asList(args.getString(2).split(","));
+
+ String partitionFilter = args.isNullAt(3) ? null : toWhere(args.getString(3));
+
+ return modifyPaimonTable(
+ tableIdent,
+ table -> {
+ Preconditions.checkArgument(table instanceof FileStoreTable);
+ InternalRow internalRow =
+ newInternalRow(
+ execute(
+ (FileStoreTable) table,
+ sortType,
+ sortColumns,
+ partitionFilter));
+ return new InternalRow[] {internalRow};
+ });
+ }
+
+ @Override
+ public String description() {
+ return "This procedure execute sort compact action on unaware-bucket table.";
+ }
+
+ private boolean execute(
+ FileStoreTable table,
+ String sortType,
+ List<String> sortColumns,
+ @Nullable String filter) {
+ CoreOptions coreOptions = table.store().options();
+
+ if (!(table instanceof AppendOnlyFileStoreTable) || coreOptions.bucket() != -1) {
+ throw new UnsupportedOperationException(
+ "Spark sort compact only support unaware-bucket append-only table yet.");
+ }
+
+ Dataset<Row> row = spark().read().format("paimon").load(coreOptions.path().getPath());
+ row = StringUtils.isBlank(filter) ? row : row.where(filter);
+ new WriteIntoPaimonTable(
+ table,
+ SaveMode.dynamic(),
+ TableSorter.getSorter(table, sortType, sortColumns).sort(row),
+ new Options())
+ .run(spark());
+ return true;
+ }
+
+ @VisibleForTesting
+ static String toWhere(String partitions) {
+ if (StringUtils.isBlank(partitions)) {
+ return null;
+ }
+
+ List<Map<String, String>> maps = ParameterUtils.getPartitions(partitions.split(";"));
+
+ return maps.stream()
Review Comment:
For compatible with flink action, but iceberg does like what you said.
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Re: [PR] [spark] Introduce spark compact procedure [incubator-paimon]
Posted by "yuzelin (via GitHub)" <gi...@apache.org>.
yuzelin commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1389014029
##########
docs/content/engines/spark3.md:
##########
@@ -425,6 +425,29 @@ val query = spark.readStream
*/
```
+## Spark Procedure
+
+This section introduce all available spark procedures about paimon.
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 4%">Procedure Name</th>
+ <th class="text-left" style="width: 4%">Usage</th>
+ <th class="text-left" style="width: 20%">Explaination</th>
+ <th class="text-left" style="width: 4%">Example</th>
+ </tr>
+ </thead>
+ <tbody style="font-size: 12px; ">
+ <tr>
+ <td>sort_compact</td>
Review Comment:
-> compact
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Re: [PR] [spark] Introduce spark sort compact procedure for unaware-bucket table [incubator-paimon]
Posted by "Zouxxyy (via GitHub)" <gi...@apache.org>.
Zouxxyy commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1388107790
##########
paimon-spark/paimon-spark-common/src/main/java/org/apache/paimon/spark/procedure/SortCompactProcedure.java:
##########
@@ -0,0 +1,164 @@
+/*
+ * 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.
+ */
+
+package org.apache.paimon.spark.procedure;
+
+import org.apache.paimon.CoreOptions;
+import org.apache.paimon.annotation.VisibleForTesting;
+import org.apache.paimon.options.Options;
+import org.apache.paimon.spark.SaveMode;
+import org.apache.paimon.spark.commands.WriteIntoPaimonTable;
+import org.apache.paimon.spark.sort.TableSorter;
+import org.apache.paimon.table.AppendOnlyFileStoreTable;
+import org.apache.paimon.table.FileStoreTable;
+import org.apache.paimon.utils.ParameterUtils;
+import org.apache.paimon.utils.Preconditions;
+import org.apache.paimon.utils.StringUtils;
+
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.connector.catalog.Identifier;
+import org.apache.spark.sql.connector.catalog.TableCatalog;
+import org.apache.spark.sql.types.DataTypes;
+import org.apache.spark.sql.types.Metadata;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+
+import javax.annotation.Nullable;
+
+import java.util.Arrays;
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
+
+import static org.apache.spark.sql.types.DataTypes.StringType;
+
+/** Sort compact procedure for sort unaware-bucket table. */
+public class SortCompactProcedure extends BaseProcedure {
+
+ private static final ProcedureParameter[] PARAMETERS =
+ new ProcedureParameter[] {
+ ProcedureParameter.required("table", StringType),
+ ProcedureParameter.required("order_type", StringType),
+ ProcedureParameter.required("columns", StringType),
+ ProcedureParameter.optional("conditions", StringType),
+ };
+
+ private static final StructType OUTPUT_TYPE =
+ new StructType(
+ new StructField[] {
+ new StructField("result", DataTypes.BooleanType, true, Metadata.empty())
+ });
+
+ protected SortCompactProcedure(TableCatalog tableCatalog) {
+ super(tableCatalog);
+ }
+
+ @Override
+ public ProcedureParameter[] parameters() {
+ return PARAMETERS;
+ }
+
+ @Override
+ public StructType outputType() {
+ return OUTPUT_TYPE;
+ }
+
+ @Override
+ public InternalRow[] call(InternalRow args) {
+ Preconditions.checkArgument(args.numFields() >= 3);
+ Identifier tableIdent = toIdentifier(args.getString(0), PARAMETERS[0].name());
+ String sortType = args.getString(1);
+ List<String> sortColumns = Arrays.asList(args.getString(2).split(","));
+
+ String partitionFilter = args.isNullAt(3) ? null : toWhere(args.getString(3));
+
+ return modifyPaimonTable(
+ tableIdent,
+ table -> {
+ Preconditions.checkArgument(table instanceof FileStoreTable);
+ InternalRow internalRow =
+ newInternalRow(
+ execute(
+ (FileStoreTable) table,
+ sortType,
+ sortColumns,
+ partitionFilter));
+ return new InternalRow[] {internalRow};
+ });
+ }
+
+ @Override
+ public String description() {
+ return "This procedure execute sort compact action on unaware-bucket table.";
+ }
+
+ private boolean execute(
+ FileStoreTable table,
+ String sortType,
+ List<String> sortColumns,
+ @Nullable String filter) {
+ CoreOptions coreOptions = table.store().options();
+
+ if (!(table instanceof AppendOnlyFileStoreTable) || coreOptions.bucket() != -1) {
+ throw new UnsupportedOperationException(
+ "Spark sort compact only support unaware-bucket append-only table yet.");
+ }
+
+ Dataset<Row> row = spark().read().format("paimon").load(coreOptions.path().getPath());
+ row = StringUtils.isBlank(filter) ? row : row.where(filter);
+ new WriteIntoPaimonTable(
+ table,
+ SaveMode.dynamic(),
+ TableSorter.getSorter(table, sortType, sortColumns).sort(row),
+ new Options())
+ .run(spark());
+ return true;
+ }
+
+ @VisibleForTesting
+ static String toWhere(String partitions) {
+ if (StringUtils.isBlank(partitions)) {
+ return null;
+ }
+
+ List<Map<String, String>> maps = ParameterUtils.getPartitions(partitions.split(";"));
+
+ return maps.stream()
Review Comment:
Why use this special format? We can directly pass a where condition string (such as p1 = a and p2 > b) and then let spark analyze it by itself.
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Re: [PR] [spark] Introduce spark sort compact procedure for unaware-bucket table [incubator-paimon]
Posted by "leaves12138 (via GitHub)" <gi...@apache.org>.
leaves12138 commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1388837880
##########
paimon-spark/paimon-spark-common/src/main/java/org/apache/paimon/spark/procedure/SortCompactProcedure.java:
##########
@@ -0,0 +1,164 @@
+/*
+ * 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.
+ */
+
+package org.apache.paimon.spark.procedure;
+
+import org.apache.paimon.CoreOptions;
+import org.apache.paimon.annotation.VisibleForTesting;
+import org.apache.paimon.options.Options;
+import org.apache.paimon.spark.SaveMode;
+import org.apache.paimon.spark.commands.WriteIntoPaimonTable;
+import org.apache.paimon.spark.sort.TableSorter;
+import org.apache.paimon.table.AppendOnlyFileStoreTable;
+import org.apache.paimon.table.FileStoreTable;
+import org.apache.paimon.utils.ParameterUtils;
+import org.apache.paimon.utils.Preconditions;
+import org.apache.paimon.utils.StringUtils;
+
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.connector.catalog.Identifier;
+import org.apache.spark.sql.connector.catalog.TableCatalog;
+import org.apache.spark.sql.types.DataTypes;
+import org.apache.spark.sql.types.Metadata;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+
+import javax.annotation.Nullable;
+
+import java.util.Arrays;
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
+
+import static org.apache.spark.sql.types.DataTypes.StringType;
+
+/** Sort compact procedure for sort unaware-bucket table. */
+public class SortCompactProcedure extends BaseProcedure {
+
+ private static final ProcedureParameter[] PARAMETERS =
+ new ProcedureParameter[] {
+ ProcedureParameter.required("table", StringType),
+ ProcedureParameter.required("order_type", StringType),
+ ProcedureParameter.required("columns", StringType),
+ ProcedureParameter.optional("conditions", StringType),
+ };
+
+ private static final StructType OUTPUT_TYPE =
+ new StructType(
+ new StructField[] {
+ new StructField("result", DataTypes.BooleanType, true, Metadata.empty())
+ });
+
+ protected SortCompactProcedure(TableCatalog tableCatalog) {
+ super(tableCatalog);
+ }
+
+ @Override
+ public ProcedureParameter[] parameters() {
+ return PARAMETERS;
+ }
+
+ @Override
+ public StructType outputType() {
+ return OUTPUT_TYPE;
+ }
+
+ @Override
+ public InternalRow[] call(InternalRow args) {
+ Preconditions.checkArgument(args.numFields() >= 3);
+ Identifier tableIdent = toIdentifier(args.getString(0), PARAMETERS[0].name());
+ String sortType = args.getString(1);
+ List<String> sortColumns = Arrays.asList(args.getString(2).split(","));
+
+ String partitionFilter = args.isNullAt(3) ? null : toWhere(args.getString(3));
+
+ return modifyPaimonTable(
+ tableIdent,
+ table -> {
+ Preconditions.checkArgument(table instanceof FileStoreTable);
+ InternalRow internalRow =
+ newInternalRow(
+ execute(
+ (FileStoreTable) table,
+ sortType,
+ sortColumns,
+ partitionFilter));
+ return new InternalRow[] {internalRow};
+ });
+ }
+
+ @Override
+ public String description() {
+ return "This procedure execute sort compact action on unaware-bucket table.";
+ }
+
+ private boolean execute(
+ FileStoreTable table,
+ String sortType,
+ List<String> sortColumns,
+ @Nullable String filter) {
+ CoreOptions coreOptions = table.store().options();
+
+ if (!(table instanceof AppendOnlyFileStoreTable) || coreOptions.bucket() != -1) {
+ throw new UnsupportedOperationException(
+ "Spark sort compact only support unaware-bucket append-only table yet.");
+ }
+
+ Dataset<Row> row = spark().read().format("paimon").load(coreOptions.path().getPath());
+ row = StringUtils.isBlank(filter) ? row : row.where(filter);
+ new WriteIntoPaimonTable(
+ table,
+ SaveMode.dynamic(),
+ TableSorter.getSorter(table, sortType, sortColumns).sort(row),
+ new Options())
+ .run(spark());
+ return true;
+ }
+
+ @VisibleForTesting
+ static String toWhere(String partitions) {
+ if (StringUtils.isBlank(partitions)) {
+ return null;
+ }
+
+ List<Map<String, String>> maps = ParameterUtils.getPartitions(partitions.split(";"));
+
+ return maps.stream()
Review Comment:
For compatible with flink action, but iceberg does like this.
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Re: [PR] [spark] Introduce spark sort compact procedure for unaware-bucket table [incubator-paimon]
Posted by "leaves12138 (via GitHub)" <gi...@apache.org>.
leaves12138 commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1388837045
##########
paimon-spark/paimon-spark-common/src/main/java/org/apache/paimon/spark/procedure/SortCompactProcedure.java:
##########
@@ -0,0 +1,164 @@
+/*
+ * 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.
+ */
+
+package org.apache.paimon.spark.procedure;
+
+import org.apache.paimon.CoreOptions;
+import org.apache.paimon.annotation.VisibleForTesting;
+import org.apache.paimon.options.Options;
+import org.apache.paimon.spark.SaveMode;
+import org.apache.paimon.spark.commands.WriteIntoPaimonTable;
+import org.apache.paimon.spark.sort.TableSorter;
+import org.apache.paimon.table.AppendOnlyFileStoreTable;
+import org.apache.paimon.table.FileStoreTable;
+import org.apache.paimon.utils.ParameterUtils;
+import org.apache.paimon.utils.Preconditions;
+import org.apache.paimon.utils.StringUtils;
+
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.connector.catalog.Identifier;
+import org.apache.spark.sql.connector.catalog.TableCatalog;
+import org.apache.spark.sql.types.DataTypes;
+import org.apache.spark.sql.types.Metadata;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+
+import javax.annotation.Nullable;
+
+import java.util.Arrays;
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
+
+import static org.apache.spark.sql.types.DataTypes.StringType;
+
+/** Sort compact procedure for sort unaware-bucket table. */
+public class SortCompactProcedure extends BaseProcedure {
Review Comment:
Renamed this to CompactProcedure, and support all compaction, but sort only works unaware-bucket table yet.
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Re: [PR] [spark] Introduce spark sort compact procedure for unaware-bucket table [incubator-paimon]
Posted by "leaves12138 (via GitHub)" <gi...@apache.org>.
leaves12138 closed pull request #2296: [spark] Introduce spark sort compact procedure for unaware-bucket table
URL: https://github.com/apache/incubator-paimon/pull/2296
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Re: [PR] [spark] Introduce spark sort compact procedure for unaware-bucket table [incubator-paimon]
Posted by "Zouxxyy (via GitHub)" <gi...@apache.org>.
Zouxxyy commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1388128061
##########
paimon-spark/paimon-spark-common/src/main/java/org/apache/paimon/spark/procedure/SortCompactProcedure.java:
##########
@@ -0,0 +1,164 @@
+/*
+ * 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.
+ */
+
+package org.apache.paimon.spark.procedure;
+
+import org.apache.paimon.CoreOptions;
+import org.apache.paimon.annotation.VisibleForTesting;
+import org.apache.paimon.options.Options;
+import org.apache.paimon.spark.SaveMode;
+import org.apache.paimon.spark.commands.WriteIntoPaimonTable;
+import org.apache.paimon.spark.sort.TableSorter;
+import org.apache.paimon.table.AppendOnlyFileStoreTable;
+import org.apache.paimon.table.FileStoreTable;
+import org.apache.paimon.utils.ParameterUtils;
+import org.apache.paimon.utils.Preconditions;
+import org.apache.paimon.utils.StringUtils;
+
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.connector.catalog.Identifier;
+import org.apache.spark.sql.connector.catalog.TableCatalog;
+import org.apache.spark.sql.types.DataTypes;
+import org.apache.spark.sql.types.Metadata;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+
+import javax.annotation.Nullable;
+
+import java.util.Arrays;
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
+
+import static org.apache.spark.sql.types.DataTypes.StringType;
+
+/** Sort compact procedure for sort unaware-bucket table. */
+public class SortCompactProcedure extends BaseProcedure {
+
+ private static final ProcedureParameter[] PARAMETERS =
+ new ProcedureParameter[] {
+ ProcedureParameter.required("table", StringType),
+ ProcedureParameter.required("order_type", StringType),
+ ProcedureParameter.required("columns", StringType),
+ ProcedureParameter.optional("conditions", StringType),
+ };
+
+ private static final StructType OUTPUT_TYPE =
+ new StructType(
+ new StructField[] {
+ new StructField("result", DataTypes.BooleanType, true, Metadata.empty())
+ });
+
+ protected SortCompactProcedure(TableCatalog tableCatalog) {
+ super(tableCatalog);
+ }
+
+ @Override
+ public ProcedureParameter[] parameters() {
+ return PARAMETERS;
+ }
+
+ @Override
+ public StructType outputType() {
+ return OUTPUT_TYPE;
+ }
+
+ @Override
+ public InternalRow[] call(InternalRow args) {
+ Preconditions.checkArgument(args.numFields() >= 3);
+ Identifier tableIdent = toIdentifier(args.getString(0), PARAMETERS[0].name());
+ String sortType = args.getString(1);
+ List<String> sortColumns = Arrays.asList(args.getString(2).split(","));
+
+ String partitionFilter = args.isNullAt(3) ? null : toWhere(args.getString(3));
+
+ return modifyPaimonTable(
+ tableIdent,
+ table -> {
+ Preconditions.checkArgument(table instanceof FileStoreTable);
+ InternalRow internalRow =
+ newInternalRow(
+ execute(
+ (FileStoreTable) table,
+ sortType,
+ sortColumns,
+ partitionFilter));
+ return new InternalRow[] {internalRow};
+ });
+ }
+
+ @Override
+ public String description() {
+ return "This procedure execute sort compact action on unaware-bucket table.";
+ }
+
+ private boolean execute(
+ FileStoreTable table,
+ String sortType,
+ List<String> sortColumns,
+ @Nullable String filter) {
+ CoreOptions coreOptions = table.store().options();
+
+ if (!(table instanceof AppendOnlyFileStoreTable) || coreOptions.bucket() != -1) {
+ throw new UnsupportedOperationException(
+ "Spark sort compact only support unaware-bucket append-only table yet.");
+ }
+
+ Dataset<Row> row = spark().read().format("paimon").load(coreOptions.path().getPath());
+ row = StringUtils.isBlank(filter) ? row : row.where(filter);
+ new WriteIntoPaimonTable(
+ table,
+ SaveMode.dynamic(),
Review Comment:
DynamicOverWrite$.MODULE$
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Re: [PR] [spark] Introduce spark sort compact procedure for unaware-bucket table [incubator-paimon]
Posted by "Zouxxyy (via GitHub)" <gi...@apache.org>.
Zouxxyy commented on code in PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#discussion_r1388084015
##########
paimon-spark/paimon-spark-common/src/main/java/org/apache/paimon/spark/procedure/SortCompactProcedure.java:
##########
@@ -0,0 +1,164 @@
+/*
+ * 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.
+ */
+
+package org.apache.paimon.spark.procedure;
+
+import org.apache.paimon.CoreOptions;
+import org.apache.paimon.annotation.VisibleForTesting;
+import org.apache.paimon.options.Options;
+import org.apache.paimon.spark.SaveMode;
+import org.apache.paimon.spark.commands.WriteIntoPaimonTable;
+import org.apache.paimon.spark.sort.TableSorter;
+import org.apache.paimon.table.AppendOnlyFileStoreTable;
+import org.apache.paimon.table.FileStoreTable;
+import org.apache.paimon.utils.ParameterUtils;
+import org.apache.paimon.utils.Preconditions;
+import org.apache.paimon.utils.StringUtils;
+
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.connector.catalog.Identifier;
+import org.apache.spark.sql.connector.catalog.TableCatalog;
+import org.apache.spark.sql.types.DataTypes;
+import org.apache.spark.sql.types.Metadata;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+
+import javax.annotation.Nullable;
+
+import java.util.Arrays;
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
+
+import static org.apache.spark.sql.types.DataTypes.StringType;
+
+/** Sort compact procedure for sort unaware-bucket table. */
+public class SortCompactProcedure extends BaseProcedure {
Review Comment:
Why is there a procedure called sort_compact instead of using compact and then specifying something like sort_type = NONE/ORDER/ZORDER
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Re: [PR] [spark] Introduce spark compact procedure [incubator-paimon]
Posted by "Zouxxyy (via GitHub)" <gi...@apache.org>.
Zouxxyy commented on PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296#issuecomment-1813797033
+1
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Re: [PR] [spark] Introduce spark compact procedure [incubator-paimon]
Posted by "JingsongLi (via GitHub)" <gi...@apache.org>.
JingsongLi merged PR #2296:
URL: https://github.com/apache/incubator-paimon/pull/2296
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