Modified ScalaReflection.schemaFor to take primary constructor of Product when there are multiple constructors. Added test to suite which failed before but works now.
Needed for [https://github.com/apache/spark/pull/3637]
CC: marmbrus
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#3646 from jkbradley/sql-reflection and squashes the following commits:
796b2e4 [Joseph K. Bradley] Modified ScalaReflection.schemaFor to take primary constructor of Product when there are multiple constructors. Added test to suite which failed before but works now.
Different from Hive 0.12.0, in Hive 0.13.1 UDF/UDAF/UDTF (aka Hive function) objects should only be initialized once on the driver side and then serialized to executors. However, not all function objects are serializable (e.g. GenericUDF doesn't implement Serializable). Hive 0.13.1 solves this issue with Kryo or XML serializer. Several utility ser/de methods are provided in class o.a.h.h.q.e.Utilities for this purpose. In this PR we chose Kryo for efficiency. The Kryo serializer used here is created in Hive. Spark Kryo serializer wasn't used because there's no available SparkConf instance.
Author: Cheng Hao <hao.cheng@intel.com>
Author: Cheng Lian <lian@databricks.com>
Closes#3640 from chenghao-intel/udf_serde and squashes the following commits:
8e13756 [Cheng Hao] Update the comment
74466a3 [Cheng Hao] refactor as feedbacks
396c0e1 [Cheng Hao] avoid Simple UDF to be serialized
e9c3212 [Cheng Hao] update the comment
19cbd46 [Cheng Hao] support udf instance ser/de after initialization
This is the code refactor and follow ups for #2570
Author: Cheng Hao <hao.cheng@intel.com>
Closes#3336 from chenghao-intel/createtbl and squashes the following commits:
3563142 [Cheng Hao] remove the unused variable
e215187 [Cheng Hao] eliminate the compiling warning
4f97f14 [Cheng Hao] fix bug in unittest
5d58812 [Cheng Hao] revert the API changes
b85b620 [Cheng Hao] fix the regression of temp tabl not found in CTAS
Author: Jacky Li <jacky.likun@huawei.com>
Closes#3630 from jackylk/remove and squashes the following commits:
150e7e0 [Jacky Li] remove unnecessary import
Enables Kryo and disables reference tracking by default in Spark SQL Thrift server. Configurations explicitly defined by users in `spark-defaults.conf` are respected (the Thrift server is started by `spark-submit`, which handles configuration properties properly).
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Author: Cheng Lian <lian@databricks.com>
Closes#3621 from liancheng/kryo-by-default and squashes the following commits:
70c2775 [Cheng Lian] Enables Kryo by default in Spark SQL Thrift server
Author: Michael Armbrust <michael@databricks.com>
Closes#3613 from marmbrus/parquetPartitionPruning and squashes the following commits:
4f138f8 [Michael Armbrust] Use catalyst for partition pruning in newParquet.
Just found this instance while doing some jstack-based profiling of a Spark SQL job. It is very unlikely that this is causing much of a perf issue anywhere, but it is unnecessarily suboptimal.
Author: Aaron Davidson <aaron@databricks.com>
Closes#3593 from aarondav/seq-opt and squashes the following commits:
962cdfc [Aaron Davidson] [SQL] Minor: Avoid calling Seq#size in a loop
Author: Jacky Li <jacky.likun@huawei.com>
Closes#3585 from jackylk/remove and squashes the following commits:
045423d [Jacky Li] remove unnecessary import
This is a very small fix that catches one specific exception and returns an empty table. #3441 will address this in a more principled way.
Author: Michael Armbrust <michael@databricks.com>
Closes#3586 from marmbrus/fixEmptyParquet and squashes the following commits:
2781d9f [Michael Armbrust] Handle empty lists for newParquet
04dd376 [Michael Armbrust] Avoid exception when reading empty parquet data through Hive
Using ```executeCollect``` to collect the result, because executeCollect is a custom implementation of collect in spark sql which better than rdd's collect
Author: wangfei <wangfei1@huawei.com>
Closes#3547 from scwf/executeCollect and squashes the following commits:
a5ab68e [wangfei] Revert "adding debug info"
a60d680 [wangfei] fix test failure
0db7ce8 [wangfei] adding debug info
184c594 [wangfei] using executeCollect instead collect
We should use `~` instead of `-` for bitwise NOT.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#3528 from adrian-wang/symbol and squashes the following commits:
affd4ad [Daoyuan Wang] fix code gen test case
56efb79 [Daoyuan Wang] ensure bitwise NOT over byte and short persist data type
f55fbae [Daoyuan Wang] wrong symbol for bitwise not
SELECT max(1/0) FROM src
would return a very large number, which is obviously not right.
For hive-0.12, hive would return `Infinity` for 1/0, while for hive-0.13.1, it is `NULL` for 1/0.
I think it is better to keep our behavior with newer Hive version.
This PR ensures that when the divider is 0, the result of expression should be NULL, same with hive-0.13.1
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#3443 from adrian-wang/div and squashes the following commits:
2e98677 [Daoyuan Wang] fix code gen for divide 0
85c28ba [Daoyuan Wang] temp
36236a5 [Daoyuan Wang] add test cases
6f5716f [Daoyuan Wang] fix comments
cee92bd [Daoyuan Wang] avoid evaluation 2 times
22ecd9a [Daoyuan Wang] fix style
cf28c58 [Daoyuan Wang] divide fix
2dfe50f [Daoyuan Wang] return null when divider is 0 of Double type
val jsc = new org.apache.spark.api.java.JavaSparkContext(sc)
val jhc = new org.apache.spark.sql.hive.api.java.JavaHiveContext(jsc)
val nrdd = jhc.hql("select null from spark_test.for_test")
println(nrdd.schema)
Then the error is thrown as follows:
scala.MatchError: NullType (of class org.apache.spark.sql.catalyst.types.NullType$)
at org.apache.spark.sql.types.util.DataTypeConversions$.asJavaDataType(DataTypeConversions.scala:43)
Author: YanTangZhai <hakeemzhai@tencent.com>
Author: yantangzhai <tyz0303@163.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#3538 from YanTangZhai/MatchNullType and squashes the following commits:
e052dff [yantangzhai] [SPARK-4676] [SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql has null
4b4bb34 [yantangzhai] [SPARK-4676] [SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql has null
896c7b7 [yantangzhai] fix NullType MatchError in JavaSchemaRDD when sql has null
6e643f8 [YanTangZhai] Merge pull request #11 from apache/master
e249846 [YanTangZhai] Merge pull request #10 from apache/master
d26d982 [YanTangZhai] Merge pull request #9 from apache/master
76d4027 [YanTangZhai] Merge pull request #8 from apache/master
03b62b0 [YanTangZhai] Merge pull request #7 from apache/master
8a00106 [YanTangZhai] Merge pull request #6 from apache/master
cbcba66 [YanTangZhai] Merge pull request #3 from apache/master
cdef539 [YanTangZhai] Merge pull request #1 from apache/master
Author: baishuo <vc_java@hotmail.com>
Closes#3526 from baishuo/master-trycatch and squashes the following commits:
d446e14 [baishuo] correct the code style
b36bf96 [baishuo] correct the code style
ae0e447 [baishuo] add finally to avoid resource leak
Spark SQL has embeded sqrt and abs but DSL doesn't support those functions.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#3401 from sarutak/dsl-missing-operator and squashes the following commits:
07700cf [Kousuke Saruta] Modified Literal(null, NullType) to Literal(null) in DslQuerySuite
8f366f8 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into dsl-missing-operator
1b88e2e [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into dsl-missing-operator
0396f89 [Kousuke Saruta] Added sqrt and abs to Spark SQL DSL
A very small nit update.
Author: Reynold Xin <rxin@databricks.com>
Closes#3552 from rxin/license-header and squashes the following commits:
df8d1a4 [Reynold Xin] Indent license header properly for interfaces.scala.
In addition, using `s.isEmpty` to eliminate the string comparison.
Author: zsxwing <zsxwing@gmail.com>
Closes#3132 from zsxwing/SPARK-4268 and squashes the following commits:
358e235 [zsxwing] Improvement of allCaseVersions
Support view definition like
CREATE VIEW view3(valoo)
TBLPROPERTIES ("fear" = "factor")
AS SELECT upper(value) FROM src WHERE key=86;
[valoo as the alias of upper(value)]. This is missing part of SPARK-4239, for a fully view support.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#3396 from adrian-wang/viewcolumn and squashes the following commits:
4d001d0 [Daoyuan Wang] support view with column alias
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#3516 from ravipesala/ddl_doc and squashes the following commits:
d101fdf [ravipesala] Style issues fixed
d2238cd [ravipesala] Corrected documentation
Supporting multi column support in countDistinct function like count(distinct c1,c2..) in Spark SQL
Author: ravipesala <ravindra.pesala@huawei.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#3511 from ravipesala/countdistinct and squashes the following commits:
cc4dbb1 [ravipesala] style
070e12a [ravipesala] Supporting multi column support in count(distinct c1,c2..) in Spark SQL
Remove hardcoding max and min values for types. Let BigDecimal do checking type compatibility.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#3208 from viirya/more_numericLit and squashes the following commits:
e9834b4 [Liang-Chi Hsieh] Remove byte and short types for number literal.
1bd1825 [Liang-Chi Hsieh] Fix Indentation and make the modification clearer.
cf1a997 [Liang-Chi Hsieh] Modified for comment to add a rule of analysis that adds a cast.
91fe489 [Liang-Chi Hsieh] add Byte and Short.
1bdc69d [Liang-Chi Hsieh] Let BigDecimal do checking type compatibility.
group tab is missing for scaladoc
Author: Jacky Li <jacky.likun@gmail.com>
Closes#3458 from jackylk/patch-7 and squashes the following commits:
0121a70 [Jacky Li] add @group tab in limit() and count()
Author: zsxwing <zsxwing@gmail.com>
Closes#3521 from zsxwing/SPARK-4661 and squashes the following commits:
03cbe3f [zsxwing] Minor code and docs cleanup
This PR disables HiveThriftServer2 asynchronous execution by setting `runInBackground` argument in `ExecuteStatementOperation` to `false`, and reverting `SparkExecuteStatementOperation.run` in Hive 13 shim to Hive 12 version. This change makes Simba ODBC driver v1.0.0.1000 work.
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Author: Cheng Lian <lian@databricks.com>
Closes#3506 from liancheng/disable-async-exec and squashes the following commits:
593804d [Cheng Lian] Disables asynchronous execution in Hive 0.13.1 HiveThriftServer2
```timeTaken``` should not count the time of printing result.
Author: w00228970 <wangfei1@huawei.com>
Closes#3423 from scwf/time-taken-bug and squashes the following commits:
da7e102 [w00228970] compute time taken correctly
Re-implement the Python broadcast using file:
1) serialize the python object using cPickle, write into disks.
2) Create a wrapper in JVM (for the dumped file), it read data from during serialization
3) Using TorrentBroadcast or HttpBroadcast to transfer the data (compressed) into executors
4) During deserialization, writing the data into disk.
5) Passing the path into Python worker, read data from disk and unpickle it into python object, until the first access.
It fixes the performance regression introduced in #2659, has similar performance as 1.1, but support object larger than 2G, also improve the memory efficiency (only one compressed copy in driver and executor).
Testing with a 500M broadcast and 4 tasks (excluding the benefit from reused worker in 1.2):
name | 1.1 | 1.2 with this patch | improvement
---------|--------|---------|--------
python-broadcast-w-bytes | 25.20 | 9.33 | 170.13% |
python-broadcast-w-set | 4.13 | 4.50 | -8.35% |
Testing with 100 tasks (16 CPUs):
name | 1.1 | 1.2 with this patch | improvement
---------|--------|---------|--------
python-broadcast-w-bytes | 38.16 | 8.40 | 353.98%
python-broadcast-w-set | 23.29 | 9.59 | 142.80%
Author: Davies Liu <davies@databricks.com>
Closes#3417 from davies/pybroadcast and squashes the following commits:
50a58e0 [Davies Liu] address comments
b98de1d [Davies Liu] disable gc while unpickle
e5ee6b9 [Davies Liu] support large string
09303b8 [Davies Liu] read all data into memory
dde02dd [Davies Liu] improve performance of python broadcast
When we use ORDER BY clause, at first, attributes referenced by projection are resolved (1).
And then, attributes referenced at ORDER BY clause are resolved (2).
But when resolving attributes referenced at ORDER BY clause, the resolution result generated in (1) is discarded so for example, following query fails.
SELECT c1 + c2 FROM mytable ORDER BY c1;
The query above fails because when resolving the attribute reference 'c1', the resolution result of 'c2' is discarded.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#3363 from sarutak/SPARK-4487 and squashes the following commits:
fd314f3 [Kousuke Saruta] Fixed attribute resolution logic in Analyzer
6e60c20 [Kousuke Saruta] Fixed conflicts
cb5b7e9 [Kousuke Saruta] Added test case for SPARK-4487
282d529 [Kousuke Saruta] Fixed attributes reference resolution error
b6123e6 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into concat-feature
317b7fb [Kousuke Saruta] WIP
This file is for Hive 0.13.1 I think.
Author: Daniel Darabos <darabos.daniel@gmail.com>
Closes#3432 from darabos/patch-2 and squashes the following commits:
4fd22ed [Daniel Darabos] Fix comment. This file is for Hive 0.13.1.
This PR is a workaround for SPARK-4479. Two changes are introduced: when merge sort is bypassed in `ExternalSorter`,
1. also bypass RDD elements buffering as buffering is the reason that `MutableRow` backed row objects must be copied, and
2. avoids defensive copies in `Exchange` operator
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Author: Cheng Lian <lian@databricks.com>
Closes#3422 from liancheng/avoids-defensive-copies and squashes the following commits:
591f2e9 [Cheng Lian] Passes all shuffle suites
0c3c91e [Cheng Lian] Fixes shuffle write metrics when merge sort is bypassed
ed5df3c [Cheng Lian] Fixes styling changes
f75089b [Cheng Lian] Avoids unnecessary defensive copies when sort based shuffle is on
This is just a quick fix for 1.2. SPARK-4523 describes a more complete solution.
Author: Michael Armbrust <michael@databricks.com>
Closes#3392 from marmbrus/parquetMetadata and squashes the following commits:
bcc6626 [Michael Armbrust] Parse schema with missing metadata.
Goals:
- Support for accessing parquet using SQL but not requiring Hive (thus allowing support of parquet tables with decimal columns)
- Support for folder based partitioning with automatic discovery of available partitions
- Caching of file metadata
See scaladoc of `ParquetRelation2` for more details.
Author: Michael Armbrust <michael@databricks.com>
Closes#3269 from marmbrus/newParquet and squashes the following commits:
1dd75f1 [Michael Armbrust] Pass all paths for FileInputFormat at once.
645768b [Michael Armbrust] Review comments.
abd8e2f [Michael Armbrust] Alternative implementation of parquet based on the datasources API.
938019e [Michael Armbrust] Add an experimental interface to data sources that exposes catalyst expressions.
e9d2641 [Michael Armbrust] logging / formatting improvements.
Query `SELECT named_struct(lower("AA"), "12", lower("Bb"), "13") FROM src LIMIT 1` will throw exception, some of the Hive Generic UDF/UDAF requires the input object inspector is `ConstantObjectInspector`, however, we won't get that before the expression optimization executed. (Constant Folding).
This PR is a work around to fix this. (As ideally, the `output` of LogicalPlan should be identical before and after Optimization).
Author: Cheng Hao <hao.cheng@intel.com>
Closes#3109 from chenghao-intel/optimized and squashes the following commits:
487ff79 [Cheng Hao] rebase to the latest master & update the unittest
Sample code in the description of SchemaRDD.where is not correct
Author: Jacky Li <jacky.likun@gmail.com>
Closes#3344 from jackylk/patch-6 and squashes the following commits:
62cd126 [Jacky Li] [SQL] fix function description mistake
Hive supports the `explain` the CTAS, which was supported by Spark SQL previously, however, seems it was reverted after the code refactoring in HiveQL.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#3357 from chenghao-intel/explain and squashes the following commits:
7aace63 [Cheng Hao] Support the CTAS in EXPLAIN command
Executing sum distinct for empty table throws `java.lang.UnsupportedOperationException: empty.reduceLeft`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#3184 from ueshin/issues/SPARK-4318 and squashes the following commits:
8168c42 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-4318
66fdb0a [Takuya UESHIN] Re-refine aggregate functions.
6186eb4 [Takuya UESHIN] Fix Sum of GeneratedAggregate.
d2975f6 [Takuya UESHIN] Refine Sum and Average of GeneratedAggregate.
1bba675 [Takuya UESHIN] Refine Sum, SumDistinct and Average functions.
917e533 [Takuya UESHIN] Use aggregate instead of groupBy().
1a5f874 [Takuya UESHIN] Add tests to be executed as non-partial aggregation.
a5a57d2 [Takuya UESHIN] Fix empty Average.
22799dc [Takuya UESHIN] Fix empty Sum and SumDistinct.
65b7dd2 [Takuya UESHIN] Fix empty sum distinct.
The relational operator '<=>' is not working in Spark SQL. Same works in Spark HiveQL
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#3387 from ravipesala/<=> and squashes the following commits:
7198e90 [ravipesala] Supporting relational operator '<=>' in Spark SQL
This PR enables the Web UI storage tab to show the in-memory table name instead of the mysterious query plan string as the name of the in-memory columnar RDD.
Note that after #2501, a single columnar RDD can be shared by multiple in-memory tables, as long as their query results are the same. In this case, only the first cached table name is shown. For example:
```sql
CACHE TABLE first AS SELECT * FROM src;
CACHE TABLE second AS SELECT * FROM src;
```
The Web UI only shows "In-memory table first".
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Author: Cheng Lian <lian@databricks.com>
Closes#3383 from liancheng/columnar-rdd-name and squashes the following commits:
071907f [Cheng Lian] Fixes tests
12ddfa6 [Cheng Lian] Names in-memory columnar RDD with corresponding table name
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#3277 from vanzin/version-1.3 and squashes the following commits:
7c3c396 [Marcelo Vanzin] Added temp repo to sbt build.
5f404ff [Marcelo Vanzin] Add another exclusion.
19457e7 [Marcelo Vanzin] Update old version to 1.2, add temporary 1.2 repo.
3c8d705 [Marcelo Vanzin] Workaround for MIMA checks.
e940810 [Marcelo Vanzin] Bumping version to 1.3.0-SNAPSHOT.
For expressions like `10 < someVar`, we should create an `Operators.Gt` filter, but right now an `Operators.Lt` is created. This issue affects all inequality predicates with literals on the left hand side.
(This bug existed before #3317 and affects branch-1.1. #3338 was opened to backport this to branch-1.1.)
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Author: Cheng Lian <lian@databricks.com>
Closes#3334 from liancheng/fix-parquet-comp-filter and squashes the following commits:
0130897 [Cheng Lian] Fixes Parquet comparison filter generation
This patch will bring support for broadcasting objects larger than 2G.
pickle, zlib, FrameSerializer and Array[Byte] all can not support objects larger than 2G, so this patch introduce LargeObjectSerializer to serialize broadcast objects, the object will be serialized and compressed into small chunks, it also change the type of Broadcast[Array[Byte]]] into Broadcast[Array[Array[Byte]]]].
Testing for support broadcast objects larger than 2G is slow and memory hungry, so this is tested manually, could be added into SparkPerf.
Author: Davies Liu <davies@databricks.com>
Author: Davies Liu <davies.liu@gmail.com>
Closes#2659 from davies/huge and squashes the following commits:
7b57a14 [Davies Liu] add more tests for broadcast
28acff9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge
a2f6a02 [Davies Liu] bug fix
4820613 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge
5875c73 [Davies Liu] address comments
10a349b [Davies Liu] address comments
0c33016 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge
6182c8f [Davies Liu] Merge branch 'master' into huge
d94b68f [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge
2514848 [Davies Liu] address comments
fda395b [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge
1c2d928 [Davies Liu] fix scala style
091b107 [Davies Liu] broadcast objects larger than 2G
Author: Michael Armbrust <michael@databricks.com>
Closes#3272 from marmbrus/keyInPartitionedTable and squashes the following commits:
447f08c [Michael Armbrust] Support partitioned parquet tables that have the key in both the directory and the file
While reviewing PR #3083 and #3161, I noticed that Parquet record filter generation code can be simplified significantly according to the clue stated in [SPARK-4453](https://issues.apache.org/jira/browse/SPARK-4213). This PR addresses both SPARK-4453 and SPARK-4213 with this simplification.
While generating `ParquetTableScan` operator, we need to remove all Catalyst predicates that have already been pushed down to Parquet. Originally, we first generate the record filter, and then call `findExpression` to traverse the generated filter to find out all pushed down predicates [[1](64c6b9bad5/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala (L213-L228))]. In this way, we have to introduce the `CatalystFilter` class hierarchy to bind the Catalyst predicates together with their generated Parquet filter, and complicate the code base a lot.
The basic idea of this PR is that, we don't need `findExpression` after filter generation, because we already know a predicate can be pushed down if we can successfully generate its corresponding Parquet filter. SPARK-4213 is fixed by returning `None` for any unsupported predicate type.
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Author: Cheng Lian <lian@databricks.com>
Closes#3317 from liancheng/simplify-parquet-filters and squashes the following commits:
d6a9499 [Cheng Lian] Fixes import styling issue
43760e8 [Cheng Lian] Simplifies Parquet filter generation logic
Author: Cheng Hao <hao.cheng@intel.com>
Closes#3308 from chenghao-intel/unwrap_constant_oi and squashes the following commits:
156b500 [Cheng Hao] rebase the master
c5b20ab [Cheng Hao] unwrap for the ConstantObjectInspector
The `totalSize` of external table is always zero, which will influence join strategy(always use broadcast join for external table).
Author: w00228970 <wangfei1@huawei.com>
Closes#3304 from scwf/statistics and squashes the following commits:
568f321 [w00228970] fix statistics for external table
This PR is exactly the same as #3178 except it reverts the `FileStatus.isDir` to `FileStatus.isDirectory` change, since it doesn't compile with Hadoop 1.
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Author: Cheng Lian <lian@databricks.com>
Closes#3298 from liancheng/date-for-thriftserver and squashes the following commits:
866037e [Cheng Lian] Revers isDirectory to isDir (it breaks Hadoop 1 profile)
6f71d0b [Cheng Lian] Makes toHiveString static
26fa955 [Cheng Lian] Fixes complex type support in Hive 0.13.1 shim
a92882a [Cheng Lian] Updates HiveShim for 0.13.1
73f442b [Cheng Lian] Adds Date support for HiveThriftServer2 (Hive 0.12.0)
Author: Cheng Hao <hao.cheng@intel.com>
Closes#3217 from chenghao-intel/mutablerow and squashes the following commits:
e8a10bd [Cheng Hao] revert the change of Row object
4681aea [Cheng Hao] Add toMutableRow method in object Row
a751838 [Cheng Hao] Construct the MutableRow from an existed row
`Cast` from `NaN` or `Infinity` of `Double` or `Float` to `TimestampType` throws `NumberFormatException`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#3283 from ueshin/issues/SPARK-4425 and squashes the following commits:
14def0c [Takuya UESHIN] Fix Cast to be able to handle NaN or Infinity to TimestampType.
This is follow-up of [SPARK-4390](https://issues.apache.org/jira/browse/SPARK-4390) (#3256).
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#3278 from ueshin/issues/SPARK-4420 and squashes the following commits:
7fea558 [Takuya UESHIN] Add some tests.
cb2301a [Takuya UESHIN] Fix tests.
133bad5 [Takuya UESHIN] Change nullability of Cast from DoubleType/FloatType to DecimalType.