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[HUDI-4729] Fix file group pending compaction cannot be queried when …
…query _ro table (apache#6516) File group in pending compaction can not be queried when query _ro table with spark. This commit fixes that. Co-authored-by: zhanshaoxiong <shaoxiong0001@@gmail.com> Co-authored-by: Sagar Sumit <[email protected]>
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...i-spark/src/test/scala/org/apache/spark/sql/hudi/TestQueryMergeOnReadOptimizedTable.scala
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/* | ||
* 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. | ||
*/ | ||
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package org.apache.spark.sql.hudi | ||
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class TestQueryMergeOnReadOptimizedTable extends HoodieSparkSqlTestBase { | ||
test("Test Query Merge_On_Read Read_Optimized table") { | ||
withTempDir { tmp => | ||
val tableName = generateTableName | ||
val tablePath = s"${tmp.getCanonicalPath}/$tableName" | ||
// create table | ||
spark.sql( | ||
s""" | ||
|create table $tableName ( | ||
| id int, | ||
| name string, | ||
| price double, | ||
| ts long | ||
|) using hudi | ||
| partitioned by (ts) | ||
| location '$tablePath' | ||
| tblproperties ( | ||
| type = 'mor', | ||
| primaryKey = 'id', | ||
| preCombineField = 'ts' | ||
| ) | ||
""".stripMargin) | ||
// insert data to table | ||
spark.sql("set hoodie.parquet.max.file.size = 10000") | ||
spark.sql(s"insert into $tableName values(1, 'a1', 10, 1000)") | ||
spark.sql(s"insert into $tableName values(2, 'a2', 10, 1000)") | ||
spark.sql(s"insert into $tableName values(3, 'a3', 10, 1000)") | ||
spark.sql(s"insert into $tableName values(4, 'a4', 10, 1000)") | ||
spark.sql(s"update $tableName set price = 11 where id = 1") | ||
spark.sql(s"update $tableName set price = 21 where id = 2") | ||
spark.sql(s"update $tableName set price = 31 where id = 3") | ||
spark.sql(s"update $tableName set price = 41 where id = 4") | ||
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// expect that all complete parquet files can be scanned | ||
assertQueryResult(4, tablePath) | ||
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// async schedule compaction job | ||
spark.sql(s"call run_compaction(op => 'schedule', table => '$tableName')") | ||
.collect() | ||
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// expect that all complete parquet files can be scanned with a pending compaction job | ||
assertQueryResult(4, tablePath) | ||
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spark.sql(s"insert into $tableName values(5, 'a5', 10, 1000)") | ||
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// expect that all complete parquet files can be scanned with a pending compaction job | ||
assertQueryResult(5, tablePath) | ||
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// async run compaction job | ||
spark.sql(s"call run_compaction(op => 'run', table => '$tableName')") | ||
.collect() | ||
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// assert that all complete parquet files can be scanned after compaction | ||
assertQueryResult(5, tablePath) | ||
} | ||
} | ||
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def assertQueryResult(expected: Any, | ||
tablePath: String): Unit = { | ||
val actual = spark.read.format("org.apache.hudi").option("hoodie.datasource.query.type", "read_optimized").load(tablePath).count() | ||
assertResult(expected)(actual) | ||
} | ||
} |