'(' and ')' are special characters used in Parquet schema for type annotation. When we run an aggregation query, we will obtain attribute name such as "MAX(a)".
If we directly store the generated DataFrame as Parquet file, it causes failure when reading and parsing the stored schema string.
Several methods can be adopted to solve this. This pr uses a simplest one to just replace attribute names before generating Parquet schema based on these attributes.
Another possible method might be modifying all aggregation expression names from "func(column)" to "func[column]".
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#5263 from viirya/parquet_aggregation_name and squashes the following commits:
2d70542 [Liang-Chi Hsieh] Address comment.
463dff4 [Liang-Chi Hsieh] Instead of replacing special chars, showing error message to user to suggest using Alias.
1de001d [Liang-Chi Hsieh] Replace special characters '(' and ')' of Parquet schema.
When union non-decimal types with decimals, we use the following rules:
- FIRST `intTypeToFixed`, then fixed union decimals with precision/scale p1/s2 and p2/s2 will be promoted to
DecimalType(max(p1, p2), max(s1, s2))
- FLOAT and DOUBLE cause fixed-length decimals to turn into DOUBLE (this is the same as Hive,
but note that unlimited decimals are considered bigger than doubles in WidenTypes)
Author: guowei2 <guowei2@asiainfo.com>
Closes#4004 from guowei2/SPARK-5203 and squashes the following commits:
ff50f5f [guowei2] fix code style
11df1bf [guowei2] fix decimal union with double, double->Decimal(15,15)
0f345f9 [guowei2] fix structType merge with decimal
101ed4d [guowei2] fix build error after rebase
0b196e4 [guowei2] code style
fe2c2ca [guowei2] handle union decimal precision in 'DecimalPrecision'
421d840 [guowei2] fix union types for decimal precision
ef2c661 [guowei2] fix union with different decimal type
Just fix a typo.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#5352 from viirya/fix_a_typo and squashes the following commits:
303b2d2 [Liang-Chi Hsieh] Fix typo.
This builds on my earlier pull requests and turns on the explicit type checking in scalastyle.
Author: Reynold Xin <rxin@databricks.com>
Closes#5342 from rxin/SPARK-6428 and squashes the following commits:
7b531ab [Reynold Xin] import ordering
2d9a8a5 [Reynold Xin] jl
e668b1c [Reynold Xin] override
9b9e119 [Reynold Xin] Parenthesis.
82e0cf5 [Reynold Xin] [SPARK-6428] Turn on explicit type checking for public methods.
https://issues.apache.org/jira/browse/SPARK-6575
Author: Yin Huai <yhuai@databricks.com>
This patch had conflicts when merged, resolved by
Committer: Cheng Lian <lian@databricks.com>
Closes#5339 from yhuai/parquetRelationCache and squashes the following commits:
b0e1a42 [Yin Huai] Address comments.
83d9846 [Yin Huai] Remove unnecessary change.
c0dc7a4 [Yin Huai] Cache converted parquet relations.
NotImplementedError in scala 2.10 is a fatal exception, which is not very nice to throw when not actually fatal.
Author: Michael Armbrust <michael@databricks.com>
Closes#5315 from marmbrus/throwUnsupported and squashes the following commits:
c29e03b [Michael Armbrust] [SQL] Throw UnsupportedOperationException instead of NotImplementedError
052e05b [Michael Armbrust] [SQL] Throw UnsupportedOperationException instead of NotImplementedError
In order to do inbound checking and type conversion, we should use Literal.create() instead of constructor.
Author: Davies Liu <davies@databricks.com>
Closes#5320 from davies/literal and squashes the following commits:
1667604 [Davies Liu] fix style and add comment
5f8c0fd [Davies Liu] use Literal.create instread of constructor
1. Test JARs are built & published
1. log4j.resources is explicitly excluded. Without this, downstream test run logging depends on the order the JARs are listed/loaded
1. sql/hive pulls in spark-sql &...spark-catalyst for its test runs
1. The copied in test classes were rm'd, and a test edited to remove its now duplicate assert method
1. Spark streaming is now build with the same plugin/phase as the rest, but its shade plugin declaration is kept in (so different from the rest of the test plugins). Due to (#2), this means the test JAR no longer includes its log4j file.
Outstanding issues:
* should the JARs be shaded? `spark-streaming-test.jar` does, but given these are test jars for developers only, especially in the same spark source tree, it's hard to justify.
* `maven-jar-plugin` v 2.6 was explicitly selected; without this the apache-1.4 parent template JAR version (2.4) chosen.
* Are there any other resources to exclude?
Author: Steve Loughran <stevel@hortonworks.com>
Closes#5119 from steveloughran/stevel/patches/SPARK-6433-test-jars and squashes the following commits:
81ceb01 [Steve Loughran] SPARK-6433 add a clearer comment explaining what the plugin is doing & why
a6dca33 [Steve Loughran] SPARK-6433 : pull configuration section form archive plugin
c2b5f89 [Steve Loughran] SPARK-6433 omit "jar" goal from jar plugin
fdac51b [Steve Loughran] SPARK-6433 -002; indentation & delegate plugin version to parent
650f442 [Steve Loughran] SPARK-6433 patch 001: test JARs are built; sql/hive pulls in spark-sql & spark-catalyst for its test runs
Before it was possible for a query to flip back and forth from a resolved state, allowing resolution to propagate up before coercion had stabilized. The issue was that `ResolvedReferences` would run after `FunctionArgumentConversion`, but before `PropagateTypes` had run. This PR ensures we correctly `PropagateTypes` after any coercion has applied.
Author: Michael Armbrust <michael@databricks.com>
Closes#5278 from marmbrus/unionNull and squashes the following commits:
dc3581a [Michael Armbrust] [SPARK-5371][SQL] Propogate types after function conversion / before futher resolution
Consider a metastore Parquet table that
1. doesn't have schema evolution issue
2. has lots of data files and/or partitions
In this case, driver schema merging can be both slow and unnecessary. Would be good to have a configuration to let the use disable schema merging when converting such a metastore Parquet table.
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Author: Cheng Lian <lian@databricks.com>
Closes#5231 from liancheng/spark-6575 and squashes the following commits:
cd96159 [Cheng Lian] Adds configuration to disable schema merging while converting metastore Parquet tables
Also removes temporary workarounds made in #5183 and #5251.
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Author: Cheng Lian <lian@databricks.com>
Closes#5289 from liancheng/spark-6555 and squashes the following commits:
d0095ac [Cheng Lian] Removes unused imports
cfafeeb [Cheng Lian] Removes outdated comment
75a2746 [Cheng Lian] Overrides equals() and hashCode() for MetastoreRelation
JIRA: https://issues.apache.org/jira/browse/SPARK-6618
Author: Yin Huai <yhuai@databricks.com>
Closes#5281 from yhuai/lookupRelationLock and squashes the following commits:
591b4be [Yin Huai] A test?
b3a9625 [Yin Huai] Just protect client.
This PR leverages the output commit coordinator introduced in #4066 to help committing Hive and Parquet tables.
This PR extracts output commit code in `SparkHadoopWriter.commit` to `SparkHadoopMapRedUtil.commitTask`, and reuses it for committing Parquet and Hive tables on executor side.
TODO
- [ ] Add tests
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Author: Cheng Lian <lian@databricks.com>
Closes#5139 from liancheng/spark-6369 and squashes the following commits:
72eb628 [Cheng Lian] Fixes typo in javadoc
9a4b82b [Cheng Lian] Adds javadoc and addresses @aarondav's comments
dfdf3ef [Cheng Lian] Uses commit coordinator to help committing Hive and Parquet tables
Now that we have `DataFrame`s it is possible to have multiple copies in a single query plan. As such, it needs to inherit from `MultiInstanceRelation` or self joins will break. I also add better debugging errors when our self join handling fails in case there are future bugs.
Author: Michael Armbrust <michael@databricks.com>
Closes#5251 from marmbrus/multiMetaStore and squashes the following commits:
4272f6d [Michael Armbrust] [SPARK-6595][SQL] MetastoreRelation should be MuliInstanceRelation
Author: Reynold Xin <rxin@databricks.com>
Closes#5226 from rxin/empty-df and squashes the following commits:
1306d88 [Reynold Xin] Proper fix.
e135bb9 [Reynold Xin] [SPARK-6564][SQL] SQLContext.emptyDataFrame should contain 0 rows, not 1 row.
If the tests in "sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala" are running before CachedTableSuite.scala, the test("Drop cached table") will failed. Because the table test is created in SQLQuerySuite.scala ,and this table not droped. So when running "drop cached table", table test already exists.
There is error info:
01:18:35.738 ERROR hive.ql.exec.DDLTask: org.apache.hadoop.hive.ql.metadata.HiveException: AlreadyExistsException(message:Table test already exists)
at org.apache.hadoop.hive.ql.metadata.Hive.createTable(Hive.java:616)
at org.apache.hadoop.hive.ql.exec.DDLTask.createTable(DDLTask.java:4189)
at org.apache.hadoop.hive.ql.exec.DDLTask.execute(DDLTask.java:281)
at org.apache.hadoop.hive.ql.exec.Task.executeTask(Task.java:153)
at org.apache.hadoop.hive.ql.exec.TaskRunner.runSequential(TaskRunner.java:85)
at org.apache.hadoop.hive.ql.Driver.launchTask(Driver.java:1503)
at org.apache.hadoop.hive.ql.Driver.execute(Driver.java:1270)
at org.apache.hadoop.hive.ql.Driver.runInternal(Driver.java:1088)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:911)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:901)test”
And the test about "create table test" in "sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala,is:
test("SPARK-4825 save join to table") {
val testData = sparkContext.parallelize(1 to 10).map(i => TestData(i, i.toString)).toDF()
sql("CREATE TABLE test1 (key INT, value STRING)")
testData.insertInto("test1")
sql("CREATE TABLE test2 (key INT, value STRING)")
testData.insertInto("test2")
testData.insertInto("test2")
sql("CREATE TABLE test AS SELECT COUNT(a.value) FROM test1 a JOIN test2 b ON a.key = b.key")
checkAnswer(
table("test"),
sql("SELECT COUNT(a.value) FROM test1 a JOIN test2 b ON a.key = b.key").collect().toSeq)
}
Author: KaiXinXiaoLei <huleilei1@huawei.com>
Closes#5150 from KaiXinXiaoLei/testFailed and squashes the following commits:
7534b02 [KaiXinXiaoLei] The UT test of spark is failed.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#4930 from adrian-wang/testvs and squashes the following commits:
2ce590f [Daoyuan Wang] add explicit function types
b1d68bf [Daoyuan Wang] only substitute for parseSql
9c4a950 [Daoyuan Wang] add a comment explaining
18fb481 [Daoyuan Wang] enable variable substitute on test framework
Author: DoingDone9 <799203320@qq.com>
Closes#4973 from DoingDone9/sort_token and squashes the following commits:
855fa10 [DoingDone9] Update HiveQl.scala
c7080b3 [DoingDone9] Sort these tokens in alphabetic order to avoid further duplicate in HiveQl
c87e8b6 [DoingDone9] Merge pull request #3 from apache/master
cb1852d [DoingDone9] Merge pull request #2 from apache/master
c3f046f [DoingDone9] Merge pull request #1 from apache/master
In hive,the schema of partition may be difference from the table schema.When we use spark-sql to query the data of partition which schema is difference from the table schema,we will get the exceptions as the description of the [jira](https://issues.apache.org/jira/browse/SPARK-5498) .For example:
* We take a look of the schema for the partition and the table
```sql
DESCRIBE partition_test PARTITION (dt='1');
id int None
name string None
dt string None
# Partition Information
# col_name data_type comment
dt string None
```
```
DESCRIBE partition_test;
OK
id bigint None
name string None
dt string None
# Partition Information
# col_name data_type comment
dt string None
```
* run the sql
```sql
SELECT * FROM partition_test where dt='1';
```
we will get the cast exception `java.lang.ClassCastException: org.apache.spark.sql.catalyst.expressions.MutableLong cannot be cast to org.apache.spark.sql.catalyst.expressions.MutableInt`
Author: jeanlyn <jeanlyn92@gmail.com>
Closes#4289 from jeanlyn/schema and squashes the following commits:
9c8da74 [jeanlyn] fix style
b41d6b9 [jeanlyn] fix compile errors
07d84b6 [jeanlyn] Merge branch 'master' into schema
535b0b6 [jeanlyn] reduce conflicts
d6c93c5 [jeanlyn] fix bug
1e8b30c [jeanlyn] fix code style
0549759 [jeanlyn] fix code style
c879aa1 [jeanlyn] clean the code
2a91a87 [jeanlyn] add more test case and clean the code
12d800d [jeanlyn] fix code style
63d170a [jeanlyn] fix compile problem
7470901 [jeanlyn] reduce conflicts
afc7da5 [jeanlyn] make getConvertedOI compatible between 0.12.0 and 0.13.1
b1527d5 [jeanlyn] fix type mismatch
10744ca [jeanlyn] Insert a space after the start of the comment
3b27af3 [jeanlyn] SPARK-5498:fix bug when query the data when partition schema does not match table schema
The `ParquetConversions` analysis rule generates a hash map, which maps from the original `MetastoreRelation` instances to the newly created `ParquetRelation2` instances. However, `MetastoreRelation.equals` doesn't compare output attributes. Thus, if a single metastore Parquet table appears multiple times in a query, only a single entry ends up in the hash map, and the conversion is not correctly performed.
Proper fix for this issue should be overriding `equals` and `hashCode` for MetastoreRelation. Unfortunately, this breaks more tests than expected. It's possible that these tests are ill-formed from the very beginning. As 1.3.1 release is approaching, we'd like to make the change more surgical to avoid potential regressions. The proposed fix here is to make both the metastore relations and their output attributes as keys in the hash map used in ParquetConversions.
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Author: Cheng Lian <lian@databricks.com>
Closes#5183 from liancheng/spark-6450 and squashes the following commits:
3536780 [Cheng Lian] Fixes metastore Parquet table conversion
spark avoid old inteface of hive, then some udaf can not work like "org.apache.hadoop.hive.ql.udf.generic.GenericUDAFAverage"
Author: DoingDone9 <799203320@qq.com>
Closes#5131 from DoingDone9/udaf and squashes the following commits:
9de08d0 [DoingDone9] Update HiveUdfSuite.scala
49c62dc [DoingDone9] Update hiveUdfs.scala
98b134f [DoingDone9] Merge pull request #5 from apache/master
161cae3 [DoingDone9] Merge pull request #4 from apache/master
c87e8b6 [DoingDone9] Merge pull request #3 from apache/master
cb1852d [DoingDone9] Merge pull request #2 from apache/master
c3f046f [DoingDone9] Merge pull request #1 from apache/master
Previously it was okay to throw away subqueries after analysis, as we would never try to use that tree for resolution again. However, with eager analysis in `DataFrame`s this can cause errors for queries such as:
```scala
val df = Seq(1,2,3).map(i => (i, i.toString)).toDF("int", "str")
df.as('x).join(df.as('y), $"x.str" === $"y.str").groupBy("x.str").count()
```
As a result, in this PR we defer the elimination of subqueries until the optimization phase.
Author: Michael Armbrust <michael@databricks.com>
Closes#5160 from marmbrus/subqueriesInDfs and squashes the following commits:
a9bb262 [Michael Armbrust] Update Optimizer.scala
27d25bf [Michael Armbrust] fix hive tests
9137e03 [Michael Armbrust] add type
81cd597 [Michael Armbrust] Avoid eliminating subqueries until optimization
Author: Michael Armbrust <michael@databricks.com>
Closes#5155 from marmbrus/errorMessages and squashes the following commits:
b898188 [Michael Armbrust] Fix formatting of error messages.
Author: Reynold Xin <rxin@databricks.com>
Closes#5108 from rxin/hive-public-type and squashes the following commits:
a320328 [Reynold Xin] [SPARK-6428][SQL] Added explicit type for all public methods for Hive module.
This PR creates a trait `DataTypeParser` used to parse data types. This trait aims to be single place to provide the functionality of parsing data types' string representation. It is currently mixed in with `DDLParser` and `SqlParser`. It is also used to parse the data type for `DataFrame.cast` and to convert Hive metastore's data type string back to a `DataType`.
JIRA: https://issues.apache.org/jira/browse/SPARK-6250
Author: Yin Huai <yhuai@databricks.com>
Closes#5078 from yhuai/ddlKeywords and squashes the following commits:
0e66097 [Yin Huai] Special handle struct<>.
fea6012 [Yin Huai] Style.
c9733fb [Yin Huai] Create a trait to parse data types.
SELECT sum('a'), avg('a'), variance('a'), std('a') FROM src;
Should give output as
0.0 NULL NULL NULL
This fixes hive udaf_number_format.q
Author: Venkata Ramana G <ramana.gollamudihuawei.com>
Author: Venkata Ramana Gollamudi <ramana.gollamudi@huawei.com>
Closes#4466 from gvramana/sum_fix and squashes the following commits:
42e14d1 [Venkata Ramana Gollamudi] Added comments
39415c0 [Venkata Ramana Gollamudi] Handled the partitioned Sum expression scenario
df66515 [Venkata Ramana Gollamudi] code style fix
4be2606 [Venkata Ramana Gollamudi] Add udaf_number_format to whitelist and golden answer
330fd64 [Venkata Ramana Gollamudi] fix sum function for all null data
Use `Utils.createTempDir()` to replace other temp file mechanisms used in some tests, to further ensure they are cleaned up, and simplify
Author: Sean Owen <sowen@cloudera.com>
Closes#5029 from srowen/SPARK-6338 and squashes the following commits:
27b740a [Sean Owen] Fix hive-thriftserver tests that don't expect an existing dir
4a212fa [Sean Owen] Standardize a bit more temp dir management
9004081 [Sean Owen] Revert some added recursive-delete calls
57609e4 [Sean Owen] Use Utils.createTempDir() to replace other temp file mechanisms used in some tests, to further ensure they are cleaned up, and simplify
We need to handle ambiguous `exprId`s that are produced by new aliases as well as those caused by leaf nodes (`MultiInstanceRelation`).
Attempting to fix this revealed a bug in `equals` for `Alias` as these objects were comparing equal even when the expression ids did not match. Additionally, `LocalRelation` did not correctly provide statistics, and some tests in `catalyst` and `hive` were not using the helper functions for comparing plans.
Based on #4991 by chenghao-intel
Author: Michael Armbrust <michael@databricks.com>
Closes#5062 from marmbrus/selfJoins and squashes the following commits:
8e9b84b [Michael Armbrust] check qualifier too
8038a36 [Michael Armbrust] handle aggs too
0b9c687 [Michael Armbrust] fix more tests
c3c574b [Michael Armbrust] revert change.
725f1ab [Michael Armbrust] add statistics
a925d08 [Michael Armbrust] check for conflicting attributes in join resolution
b022ef7 [Michael Armbrust] Handle project aliases.
d8caa40 [Michael Armbrust] test case: SPARK-6247
f9c67c2 [Michael Armbrust] Check for duplicate attributes in join resolution.
898af73 [Michael Armbrust] Fix Alias equality.
Now spark version is only support
```create table table_in_database_creation.test1 as select * from src limit 1;``` in HiveContext.
This patch is used to support
```create table `table_in_database_creation.test2` as select * from src limit 1;``` in HiveContext.
Author: watermen <qiyadong2010@gmail.com>
Author: q00251598 <qiyadong@huawei.com>
Closes#4427 from watermen/SPARK-5651 and squashes the following commits:
c5c8ed1 [watermen] add the generated golden files
1f0e42e [q00251598] add input64 in blacklist and add test suit
`ResolveUdtfsAlias` in `hiveUdfs` only considers the `HiveGenericUdtf` with multiple alias. When only single alias is used with `HiveGenericUdtf`, the alias is not working.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#4692 from viirya/udft_alias and squashes the following commits:
8a3bae4 [Liang-Chi Hsieh] No need to test selected column from DataFrame since DataFrame API is updated.
160a379 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into udft_alias
e6531cc [Liang-Chi Hsieh] Selected column from DataFrame should not re-analyze logical plan.
a45cc2a [Liang-Chi Hsieh] Resolve UdtfsAlias when only single Alias is used.
---- comment;
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#4500 from adrian-wang/semicolon and squashes the following commits:
70b8abb [Daoyuan Wang] use mkstring instead of reduce
2d49738 [Daoyuan Wang] remove outdated golden file
317346e [Daoyuan Wang] only skip comment with semicolon at end of line, to avoid golden file outdated
d3ae01e [Daoyuan Wang] fix error
a11602d [Daoyuan Wang] fix comment with semicolon at end
Still, we keep only a single HiveContext within ThriftServer, and we also create a object called `SQLSession` for isolating the different user states.
Developers can obtain/release a new user session via `openSession` and `closeSession`, and `SQLContext` and `HiveContext` will also provide a default session if no `openSession` called, for backward-compatibility.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#4885 from chenghao-intel/multisessions_singlecontext and squashes the following commits:
1c47b2a [Cheng Hao] rename the tss => tlSession
815b27a [Cheng Hao] code style issue
57e3fa0 [Cheng Hao] openSession is not compatible between Hive0.12 & 0.13.1
4665b0d [Cheng Hao] thriftservice with single context
Resolve javac, scalac warnings of various types -- deprecations, Scala lang, unchecked cast, etc.
Author: Sean Owen <sowen@cloudera.com>
Closes#4950 from srowen/SPARK-6225 and squashes the following commits:
3080972 [Sean Owen] Ordered imports: Java, Scala, 3rd party, Spark
c67985b [Sean Owen] Resolve javac, scalac warnings of various types -- deprecations, Scala lang, unchecked cast, etc.
Option 1 of 2: Convert spark-parent module name to spark-parent_2.10 / spark-parent_2.11
Author: Sean Owen <sowen@cloudera.com>
Closes#4912 from srowen/SPARK-6182.1 and squashes the following commits:
eff60de [Sean Owen] Convert spark-parent module name to spark-parent_2.10 / spark-parent_2.11
- Various Fixes to docs
- Make data source traits actually interfaces
Based on #4862 but with fixed conflicts.
Author: Reynold Xin <rxin@databricks.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#4868 from marmbrus/pr/4862 and squashes the following commits:
fe091ea [Michael Armbrust] Merge remote-tracking branch 'origin/master' into pr/4862
0208497 [Reynold Xin] Test fixes.
34e0a28 [Reynold Xin] [SPARK-5310][SQL] Various fixes to Spark SQL docs.
This PR contains the following changes:
1. Add a new method, `DataType.equalsIgnoreCompatibleNullability`, which is the middle ground between DataType's equality check and `DataType.equalsIgnoreNullability`. For two data types `from` and `to`, it does `equalsIgnoreNullability` as well as if the nullability of `from` is compatible with that of `to`. For example, the nullability of `ArrayType(IntegerType, containsNull = false)` is compatible with that of `ArrayType(IntegerType, containsNull = true)` (for an array without null values, we can always say it may contain null values). However, the nullability of `ArrayType(IntegerType, containsNull = true)` is incompatible with that of `ArrayType(IntegerType, containsNull = false)` (for an array that may have null values, we cannot say it does not have null values).
2. For the `resolved` field of `InsertIntoTable`, use `equalsIgnoreCompatibleNullability` to replace the equality check of the data types.
3. For our data source write path, when appending data, we always use the schema of existing table to write the data. This is important for parquet, since nullability direct impacts the way to encode/decode values. If we do not do this, we may see corrupted values when reading values from a set of parquet files generated with different nullability settings.
4. When generating a new parquet table, we always set nullable/containsNull/valueContainsNull to true. So, we will not face situations that we cannot append data because containsNull/valueContainsNull in an Array/Map column of the existing table has already been set to `false`. This change makes the whole data pipeline more robust.
5. Update the equality check of JSON relation. Since JSON does not really cares nullability, `equalsIgnoreNullability` seems a better choice to compare schemata from to JSON tables.
JIRA: https://issues.apache.org/jira/browse/SPARK-5950
Thanks viirya for the initial work in #4729.
cc marmbrus liancheng
Author: Yin Huai <yhuai@databricks.com>
Closes#4826 from yhuai/insertNullabilityCheck and squashes the following commits:
3b61a04 [Yin Huai] Revert change on equals.
80e487e [Yin Huai] asNullable in UDT.
587d88b [Yin Huai] Make methods private.
0cb7ea2 [Yin Huai] marmbrus's comments.
3cec464 [Yin Huai] Cheng's comments.
486ed08 [Yin Huai] Merge remote-tracking branch 'upstream/master' into insertNullabilityCheck
d3747d1 [Yin Huai] Remove unnecessary change.
8360817 [Yin Huai] Merge remote-tracking branch 'upstream/master' into insertNullabilityCheck
8a3f237 [Yin Huai] Use equalsIgnoreNullability instead of equality check.
0eb5578 [Yin Huai] Fix tests.
f6ed813 [Yin Huai] Update old parquet path.
e4f397c [Yin Huai] Unit tests.
b2c06f8 [Yin Huai] Ignore nullability in JSON relation's equality check.
8bd008b [Yin Huai] nullable, containsNull, and valueContainsNull will be always true for parquet data.
bf50d73 [Yin Huai] When appending data, we use the schema of the existing table instead of the schema of the new data.
0a703e7 [Yin Huai] Test failed again since we cannot read correct content.
9a26611 [Yin Huai] Make InsertIntoTable happy.
8f19fe5 [Yin Huai] equalsIgnoreCompatibleNullability
4ec17fd [Yin Huai] Failed test.
Author: Michael Armbrust <michael@databricks.com>
Closes#4855 from marmbrus/explodeBug and squashes the following commits:
a712249 [Michael Armbrust] [SPARK-6114][SQL] Avoid metastore conversions before plan is resolved
HiveQL expression like `select count(1) from src tablesample(1 percent);` means take 1% sample to select. But it means 100% in the current version of the Spark.
Author: q00251598 <qiyadong@huawei.com>
Closes#4789 from watermen/SPARK-6040 and squashes the following commits:
2453ebe [q00251598] check and adjust the fraction.
When run ```select * from nzhang_part where hr = 'file,';```, it throws exception ```java.lang.IllegalArgumentException: Can not create a Path from an empty string```
. Because the path of hdfs contains comma, and FileInputFormat.setInputPaths will split path by comma.
### SQL
```
set hive.merge.mapfiles=true;
set hive.merge.mapredfiles=true;
set hive.input.format=org.apache.hadoop.hive.ql.io.HiveInputFormat;
set hive.exec.dynamic.partition=true;
set hive.exec.dynamic.partition.mode=nonstrict;
create table nzhang_part like srcpart;
insert overwrite table nzhang_part partition (ds='2010-08-15', hr) select key, value, hr from srcpart where ds='2008-04-08';
insert overwrite table nzhang_part partition (ds='2010-08-15', hr=11) select key, value from srcpart where ds='2008-04-08';
insert overwrite table nzhang_part partition (ds='2010-08-15', hr)
select * from (
select key, value, hr from srcpart where ds='2008-04-08'
union all
select '1' as key, '1' as value, 'file,' as hr from src limit 1) s;
select * from nzhang_part where hr = 'file,';
```
### Error Log
```
15/02/10 14:33:16 ERROR SparkSQLDriver: Failed in [select * from nzhang_part where hr = 'file,']
java.lang.IllegalArgumentException: Can not create a Path from an empty string
at org.apache.hadoop.fs.Path.checkPathArg(Path.java:127)
at org.apache.hadoop.fs.Path.<init>(Path.java:135)
at org.apache.hadoop.util.StringUtils.stringToPath(StringUtils.java:241)
at org.apache.hadoop.mapred.FileInputFormat.setInputPaths(FileInputFormat.java:400)
at org.apache.spark.sql.hive.HadoopTableReader$.initializeLocalJobConfFunc(TableReader.scala:251)
at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$11.apply(TableReader.scala:229)
at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$11.apply(TableReader.scala:229)
at org.apache.spark.rdd.HadoopRDD$$anonfun$getJobConf$6.apply(HadoopRDD.scala:172)
at org.apache.spark.rdd.HadoopRDD$$anonfun$getJobConf$6.apply(HadoopRDD.scala:172)
at scala.Option.map(Option.scala:145)
at org.apache.spark.rdd.HadoopRDD.getJobConf(HadoopRDD.scala:172)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:196)
Author: q00251598 <qiyadong@huawei.com>
Closes#4532 from watermen/SPARK-5741 and squashes the following commits:
9758ab1 [q00251598] fix bug
1db1a1c [q00251598] use setInputPaths(Job job, Path... inputPaths)
b788a72 [q00251598] change FileInputFormat.setInputPaths to jobConf.set and add test suite
JIRA: https://issues.apache.org/jira/browse/SPARK-6073
liancheng
Author: Yin Huai <yhuai@databricks.com>
Closes#4824 from yhuai/refreshCache and squashes the following commits:
b9542ef [Yin Huai] Refresh metadata cache in the Catalog in CreateMetastoreDataSourceAsSelect.
JIRA: https://issues.apache.org/jira/browse/SPARK-6024
Author: Yin Huai <yhuai@databricks.com>
Closes#4795 from yhuai/wideSchema and squashes the following commits:
4882e6f [Yin Huai] Address comments.
73e71b4 [Yin Huai] Address comments.
143927a [Yin Huai] Simplify code.
cc1d472 [Yin Huai] Make the schema wider.
12bacae [Yin Huai] If the JSON string of a schema is too large, split it before storing it in metastore.
e9b4f70 [Yin Huai] Failed test.
Please see JIRA (https://issues.apache.org/jira/browse/SPARK-6016) for details of the bug.
Author: Yin Huai <yhuai@databricks.com>
Closes#4775 from yhuai/parquetFooterCache and squashes the following commits:
78787b1 [Yin Huai] Remove footerCache in FilteringParquetRowInputFormat.
dff6fba [Yin Huai] Failed unit test.
