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This PR switches Spark SQL's Hive support to use the isolated hive client interface introduced by #5851, instead of directly interacting with the client. By using this isolated client we can now allow users to dynamically configure the version of Hive that they are connecting to by setting `spark.sql.hive.metastore.version` without the need recompile. This also greatly reduces the surface area for our interaction with the hive libraries, hopefully making it easier to support other versions in the future.
Jars for the desired hive version can be configured using `spark.sql.hive.metastore.jars`, which accepts the following options:
- a colon-separated list of jar files or directories for hive and hadoop.
- `builtin` - attempt to discover the jars that were used to load Spark SQL and use those. This
option is only valid when using the execution version of Hive.
- `maven` - download the correct version of hive on demand from maven.
By default, `builtin` is used for Hive 13.
This PR also removes the test step for building against Hive 12, as this will no longer be required to talk to Hive 12 metastores. However, the full removal of the Shim is deferred until a later PR.
Remaining TODOs:
- Remove the Hive Shims and inline code for Hive 13.
- Several HiveCompatibility tests are not yet passing.
- `nullformatCTAS` - As detailed below, we now are handling CTAS parsing ourselves instead of hacking into the Hive semantic analyzer. However, we currently only handle the common cases and not things like CTAS where the null format is specified.
- `combine1` now leaks state about compression somehow, breaking all subsequent tests. As such we currently add it to the blacklist
- `part_inherit_tbl_props` and `part_inherit_tbl_props_with_star` do not work anymore. We are correctly propagating the information
- "load_dyn_part14.*" - These tests pass when run on their own, but fail when run with all other tests. It seems our `RESET` mechanism may not be as robust as it used to be?
Other required changes:
- `CreateTableAsSelect` no longer carries parts of the HiveQL AST with it through the query execution pipeline. Instead, we parse CTAS during the HiveQL conversion and construct a `HiveTable`. The full parsing here is not yet complete as detailed above in the remaining TODOs. Since the operator is Hive specific, it is moved to the hive package.
- `Command` is simplified to be a trait that simply acts as a marker for a LogicalPlan that should be eagerly evaluated.
Author: Michael Armbrust <michael@databricks.com>
Closes #5876 from marmbrus/useIsolatedClient and squashes the following commits:
258d000 [Michael Armbrust] really really correct path handling
e56fd4a [Michael Armbrust] getAbsolutePath
5a259f5 [Michael Armbrust] fix typos
81bb366 [Michael Armbrust] comments from vanzin
5f3945e [Michael Armbrust] Merge remote-tracking branch 'origin/master' into useIsolatedClient
4b5cd41 [Michael Armbrust] yin's comments
f5de7de [Michael Armbrust] cleanup
11e9c72 [Michael Armbrust] better coverage in versions suite
7e8f010 [Michael Armbrust] better error messages and jar handling
e7b3941 [Michael Armbrust] more permisive checking for function registration
da91ba7 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into useIsolatedClient
5fe5894 [Michael Armbrust] fix serialization suite
81711c4 [Michael Armbrust] Initial support for running without maven
1d8ae44 [Michael Armbrust] fix final tests?
1c50813 [Michael Armbrust] more comments
a3bee70 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into useIsolatedClient
a6f5df1 [Michael Armbrust] style
ab07f7e [Michael Armbrust] WIP
4d8bf02 [Michael Armbrust] Remove hive 12 compilation
8843a25 [Michael Armbrust] [SPARK-6908] [SQL] Use isolated Hive client
(cherry picked from commit cd1d4110cfffb413ab585cf1cc8f1264243cb393)
Signed-off-by: Yin Huai <yhuai@databricks.com>
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Author: Yin Huai <yhuai@databricks.com>
Closes #5951 from yhuai/fixBuildMaven and squashes the following commits:
fdde183 [Yin Huai] Move HiveWindowFunctionQuerySuite.scala to hive compatibility dir.
(cherry picked from commit 77409967008415b7ea57e9349d296350e6519687)
Signed-off-by: Yin Huai <yhuai@databricks.com>
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Adding more information about the implementation...
This PR is adding the support of window functions to Spark SQL (specifically OVER and WINDOW clause). For every expression having a OVER clause, we use a WindowExpression as the container of a WindowFunction and the corresponding WindowSpecDefinition (the definition of a window frame, i.e. partition specification, order specification, and frame specification appearing in a OVER clause).
# Implementation #
The high level work flow of the implementation is described as follows.
* Query parsing: In the query parse process, all WindowExpressions are originally placed in the projectList of a Project operator or the aggregateExpressions of an Aggregate operator. It makes our changes to simple and keep all of parsing rules for window functions at a single place (nodesToWindowSpecification). For the WINDOWclause in a query, we use a WithWindowDefinition as the container as the mapping from the name of a window specification to a WindowSpecDefinition. This changes is similar with our common table expression support.
* Analysis: The query analysis process has three steps for window functions.
* Resolve all WindowSpecReferences by replacing them with WindowSpecReferences according to the mapping table stored in the node of WithWindowDefinition.
* Resolve WindowFunctions in the projectList of a Project operator or the aggregateExpressions of an Aggregate operator. For this PR, we use Hive's functions for window functions because we will have a major refactoring of our internal UDAFs and it is better to switch our UDAFs after that refactoring work.
* Once we have resolved all WindowFunctions, we will use ResolveWindowFunction to extract WindowExpressions from projectList and aggregateExpressions and then create a Window operator for every distinct WindowSpecDefinition. With this choice, at the execution time, we can rely on the Exchange operator to do all of work on reorganizing the table and we do not need to worry about it in the physical Window operator. An example analyzed plan is shown as follows
```
sql("""
SELECT
year, country, product, sales,
avg(sales) over(partition by product) avg_product,
sum(sales) over(partition by country) sum_country
FROM sales
ORDER BY year, country, product
""").explain(true)
== Analyzed Logical Plan ==
Sort [year#34 ASC,country#35 ASC,product#36 ASC], true
Project [year#34,country#35,product#36,sales#37,avg_product#27,sum_country#28]
Window [year#34,country#35,product#36,sales#37,avg_product#27], [HiveWindowFunction#org.apache.hadoop.hive.ql.udf.generic.GenericUDAFSum(sales#37) WindowSpecDefinition [country#35], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING AS sum_country#28], WindowSpecDefinition [country#35], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING
Window [year#34,country#35,product#36,sales#37], [HiveWindowFunction#org.apache.hadoop.hive.ql.udf.generic.GenericUDAFAverage(sales#37) WindowSpecDefinition [product#36], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING AS avg_product#27], WindowSpecDefinition [product#36], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING
Project [year#34,country#35,product#36,sales#37]
MetastoreRelation default, sales, None
```
* Query planning: In the process of query planning, we simple generate the physical Window operator based on the logical Window operator. Then, to prepare the executedPlan, the EnsureRequirements rule will add Exchange and Sort operators if necessary. The EnsureRequirements rule will analyze the data properties and try to not add unnecessary shuffle and sort. The physical plan for the above example query is shown below.
```
== Physical Plan ==
Sort [year#34 ASC,country#35 ASC,product#36 ASC], true
Exchange (RangePartitioning [year#34 ASC,country#35 ASC,product#36 ASC], 200), []
Window [year#34,country#35,product#36,sales#37,avg_product#27], [HiveWindowFunction#org.apache.hadoop.hive.ql.udf.generic.GenericUDAFSum(sales#37) WindowSpecDefinition [country#35], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING AS sum_country#28], WindowSpecDefinition [country#35], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING
Exchange (HashPartitioning [country#35], 200), [country#35 ASC]
Window [year#34,country#35,product#36,sales#37], [HiveWindowFunction#org.apache.hadoop.hive.ql.udf.generic.GenericUDAFAverage(sales#37) WindowSpecDefinition [product#36], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING AS avg_product#27], WindowSpecDefinition [product#36], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING
Exchange (HashPartitioning [product#36], 200), [product#36 ASC]
HiveTableScan [year#34,country#35,product#36,sales#37], (MetastoreRelation default, sales, None), None
```
* Execution time: At execution time, a physical Window operator buffers all rows in a partition specified in the partition spec of a OVER clause. If necessary, it also maintains a sliding window frame. The current implementation tries to buffer the input parameters of a window function according to the window frame to avoid evaluating a row multiple times.
# Future work #
Here are three improvements that are not hard to add:
* Taking advantage of the window frame specification to reduce the number of rows buffered in the physical Window operator. For some cases, we only need to buffer the rows appearing in the sliding window. But for other cases, we will not be able to reduce the number of rows buffered (e.g. ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING).
* When aRAGEN frame is used, for <value> PRECEDING and <value> FOLLOWING, it will be great if the <value> part is an expression (we can start with Literal). So, when the data type of ORDER BY expression is a FractionalType, we can support FractionalType as the type <value> (<value> still needs to be evaluated as a positive value).
* When aRAGEN frame is used, we need to support DateType and TimestampType as the data type of the expression appearing in the order specification. Then, the <value> part of <value> PRECEDING and <value> FOLLOWING can support interval types (once we support them).
This is a joint work with guowei2 and yhuai
Thanks hbutani hvanhovell for his comments
Thanks scwf for his comments and unit tests
Author: Yin Huai <yhuai@databricks.com>
Closes #5604 from guowei2/windowImplement and squashes the following commits:
76fe1c8 [Yin Huai] Implementation.
aa2b0ae [Yin Huai] Tests.
(cherry picked from commit f2c47082c3412a4cf8cbabe12585147c5ec3ea40)
Signed-off-by: Michael Armbrust <michael@databricks.com>
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Thanks for the initial work from Ishiihara in #3173
This PR introduce a new join method of sort merge join, which firstly ensure that keys of same value are in the same partition, and inside each partition the Rows are sorted by key. Then we can run down both sides together, find matched rows using [sort merge join](http://en.wikipedia.org/wiki/Sort-merge_join). In this way, we don't have to store the whole hash table of one side as hash join, thus we have less memory usage. Also, this PR would benefit from #3438 , making the sorting phrase much more efficient.
We introduced a new configuration of "spark.sql.planner.sortMergeJoin" to switch between this(`true`) and ShuffledHashJoin(`false`), probably we want the default value of it be `false` at first.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: Michael Armbrust <michael@databricks.com>
This patch had conflicts when merged, resolved by
Committer: Michael Armbrust <michael@databricks.com>
Closes #5208 from adrian-wang/smj and squashes the following commits:
2493b9f [Daoyuan Wang] fix style
5049d88 [Daoyuan Wang] propagate rowOrdering for RangePartitioning
f91a2ae [Daoyuan Wang] yin's comment: use external sort if option is enabled, add comments
f515cd2 [Daoyuan Wang] yin's comment: outputOrdering, join suite refine
ec8061b [Daoyuan Wang] minor change
413fd24 [Daoyuan Wang] Merge pull request #3 from marmbrus/pr/5208
952168a [Michael Armbrust] add type
5492884 [Michael Armbrust] copy when ordering
7ddd656 [Michael Armbrust] Cleanup addition of ordering requirements
b198278 [Daoyuan Wang] inherit ordering in project
c8e82a3 [Daoyuan Wang] fix style
6e897dd [Daoyuan Wang] hide boundReference from manually construct RowOrdering for key compare in smj
8681d73 [Daoyuan Wang] refactor Exchange and fix copy for sorting
2875ef2 [Daoyuan Wang] fix changed configuration
61d7f49 [Daoyuan Wang] add omitted comment
00a4430 [Daoyuan Wang] fix bug
078d69b [Daoyuan Wang] address comments: add comments, do sort in shuffle, and others
3af6ba5 [Daoyuan Wang] use buffer for only one side
171001f [Daoyuan Wang] change default outputordering
47455c9 [Daoyuan Wang] add apache license ...
a28277f [Daoyuan Wang] fix style
645c70b [Daoyuan Wang] address comments using sort
068c35d [Daoyuan Wang] fix new style and add some tests
925203b [Daoyuan Wang] address comments
07ce92f [Daoyuan Wang] fix ArrayIndexOutOfBound
42fca0e [Daoyuan Wang] code clean
e3ec096 [Daoyuan Wang] fix comment style..
2edd235 [Daoyuan Wang] fix outputpartitioning
57baa40 [Daoyuan Wang] fix sort eval bug
303b6da [Daoyuan Wang] fix several errors
95db7ad [Daoyuan Wang] fix brackets for if-statement
4464f16 [Daoyuan Wang] fix error
880d8e9 [Daoyuan Wang] sort merge join for spark sql
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in hiveQl
Standard syntax:
INSERT OVERWRITE TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...) [IF NOT EXISTS]] select_statement1 FROM from_statement;
INSERT INTO TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...)] select_statement1 FROM from_statement;
Hive extension (multiple inserts):
FROM from_statement
INSERT OVERWRITE TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...) [IF NOT EXISTS]] select_statement1
[INSERT OVERWRITE TABLE tablename2 [PARTITION ... [IF NOT EXISTS]] select_statement2]
[INSERT INTO TABLE tablename2 [PARTITION ...] select_statement2] ...;
FROM from_statement
INSERT INTO TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...)] select_statement1
[INSERT INTO TABLE tablename2 [PARTITION ...] select_statement2]
[INSERT OVERWRITE TABLE tablename2 [PARTITION ... [IF NOT EXISTS]] select_statement2] ...;
Hive extension (dynamic partition inserts):
INSERT OVERWRITE TABLE tablename PARTITION (partcol1[=val1], partcol2[=val2] ...) select_statement FROM from_statement;
INSERT INTO TABLE tablename PARTITION (partcol1[=val1], partcol2[=val2] ...) select_statement FROM from_statement;
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes #4865 from adrian-wang/insertoverwrite and squashes the following commits:
2fce94f [Daoyuan Wang] add assert
10ea6f3 [Daoyuan Wang] add name for boolean parameter
0bbe9b9 [Daoyuan Wang] fix failure
4391154 [Daoyuan Wang] support if not exists for insert overwrite into partition in hiveQl
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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
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table within backticks
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
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---- 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
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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
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In unit test, the table src(key INT, value STRING) is not the same as HIVE src(key STRING, value STRING)
https://github.com/apache/hive/blob/branch-0.13/data/scripts/q_test_init.sql
And in the reflect.q, test failed for expression `reflect("java.lang.Integer", "valueOf", key, 16)`, which expect the argument `key` as STRING not INT.
This PR doesn't aim to change the `src` schema, we can do that after 1.3 released, however, we probably need to re-generate all the golden files.
Author: Cheng Hao <hao.cheng@intel.com>
Closes #4584 from chenghao-intel/reflect and squashes the following commits:
e5bdc3a [Cheng Hao] Move the test case reflect into blacklist
184abfd [Cheng Hao] revert the change to table src1
d9bcf92 [Cheng Hao] Update the HiveContext Unittest
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Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes #4609 from adrian-wang/ctas and squashes the following commits:
0a75d5a [Daoyuan Wang] reorder import
93d1863 [Daoyuan Wang] add null format in ctas and set default col comment to null
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Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes #4502 from adrian-wang/utf8 and squashes the following commits:
4d7b0ee [Daoyuan Wang] remove useless import
606f981 [Daoyuan Wang] support TOK_CHARSETLITERAL in HiveQl
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The previous #3732 is reverted due to some test failure.
Have fixed that.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes #4325 from adrian-wang/datenative and squashes the following commits:
096e20d [Daoyuan Wang] fix for mixed timezone
0ed0fdc [Daoyuan Wang] fix test data
a2fdd4e [Daoyuan Wang] getDate
c37832b [Daoyuan Wang] row to catalyst
f0005b1 [Daoyuan Wang] add date in sql parser and java type conversion
024c9a6 [Daoyuan Wang] clean some import order
d6715fc [Daoyuan Wang] refactoring Date as Primitive Int internally
374abd5 [Daoyuan Wang] spark native date type support
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This reverts commit 1646f89d967913ee1f231d9606f8502d13c25804.
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Store daysSinceEpoch as an Int value(4 bytes) to represent DateType, instead of using java.sql.Date(8 bytes as Long) in catalyst row. This ensures the same comparison behavior of Hive and Catalyst.
Subsumes #3381
I thinks there are already some tests in JavaSQLSuite, and for python it will not affect python's datetime class.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes #3732 from adrian-wang/datenative and squashes the following commits:
0ed0fdc [Daoyuan Wang] fix test data
a2fdd4e [Daoyuan Wang] getDate
c37832b [Daoyuan Wang] row to catalyst
f0005b1 [Daoyuan Wang] add date in sql parser and java type conversion
024c9a6 [Daoyuan Wang] clean some import order
d6715fc [Daoyuan Wang] refactoring Date as Primitive Int internally
374abd5 [Daoyuan Wang] spark native date type support
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This change should be binary and source backward compatible since we didn't change any user facing APIs.
Author: Reynold Xin <rxin@databricks.com>
Closes #3965 from rxin/SPARK-5168-sqlconf and squashes the following commits:
42eec09 [Reynold Xin] Fix default conf value.
0ef86cc [Reynold Xin] Fix constructor ordering.
4d7f910 [Reynold Xin] Properly override config.
ccc8e6a [Reynold Xin] [SPARK-5168] Make SQLConf a field rather than mixin in SQLContext
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This is a follow up of #3396 , just add a test to white list.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes #3826 from adrian-wang/viewtest and squashes the following commits:
f105f68 [Daoyuan Wang] enable view test
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Add support for `GROUPING SETS`, `ROLLUP`, `CUBE` and the the virtual column `GROUPING__ID`.
More details on how to use the `GROUPING SETS" can be found at: https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation,+Cube,+Grouping+and+Rollup
https://issues.apache.org/jira/secure/attachment/12676811/grouping_set.pdf
The generic idea of the implementations are :
1 Replace the `ROLLUP`, `CUBE` with `GROUPING SETS`
2 Explode each of the input row, and then feed them to `Aggregate`
* Each grouping set are represented as the bit mask for the `GroupBy Expression List`, for each bit, `1` means the expression is selected, otherwise `0` (left is the lower bit, and right is the higher bit in the `GroupBy Expression List`)
* Several of projections are constructed according to the grouping sets, and within each projection(Seq[Expression), we replace those expressions with `Literal(null)` if it's not selected in the grouping set (based on the bit mask)
* Output Schema of `Explode` is `child.output :+ grouping__id`
* GroupBy Expressions of `Aggregate` is `GroupBy Expression List :+ grouping__id`
* Keep the `Aggregation expressions` the same for the `Aggregate`
The expressions substitutions happen in Logic Plan analyzing, so we will benefit from the Logical Plan optimization (e.g. expression constant folding, and map side aggregation etc.), Only an `Explosive` operator added for Physical Plan, which will explode the rows according the pre-set projections.
A known issue will be done in the follow up PR:
* Optimization `ColumnPruning` is not supported yet for `Explosive` node.
Author: Cheng Hao <hao.cheng@intel.com>
Closes #1567 from chenghao-intel/grouping_sets and squashes the following commits:
fe65fcc [Cheng Hao] Remove the extra space
3547056 [Cheng Hao] Add more doc and Simplify the Expand
a7c869d [Cheng Hao] update code as feedbacks
d23c672 [Cheng Hao] Add GroupingExpression to replace the Seq[Expression]
414b165 [Cheng Hao] revert the unnecessary changes
ec276c6 [Cheng Hao] Support Rollup/Cube/GroupingSets
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Whitelist more hive unit test:
"create_like_tbl_props"
"udf5"
"udf_java_method"
"decimal_1"
"udf_pmod"
"udf_to_double"
"udf_to_float"
"udf7" (this will fail in Hive 0.12)
Author: Cheng Hao <hao.cheng@intel.com>
Closes #3522 from chenghao-intel/unittest and squashes the following commits:
f54e4c7 [Cheng Hao] work around to clean up the hive.table.parameters.default in reset
16fee22 [Cheng Hao] Whitelist more unittest
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Currently still not support view like
CREATE VIEW view3(valoo)
TBLPROPERTIES ("fear" = "factor")
AS SELECT upper(value) FROM src WHERE key=86;
because the text in metastore for this view is like
select \`_c0\` as \`valoo\` from (select upper(\`src\`.\`value\`) from \`default\`.\`src\` where ...) \`view3\`
while catalyst cannot resolve \`_c0\` for this query.
For view without colname definition in parentheses, it works fine.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes #3131 from adrian-wang/view and squashes the following commits:
8a56fd6 [Daoyuan Wang] michael's comments
e46c056 [Daoyuan Wang] add some golden file
079290a [Daoyuan Wang] remove useless import
88afcad [Daoyuan Wang] support view in HiveQl
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In HQL, we convert all of the data type into normal `ObjectInspector`s for UDFs, most of cases it works, however, some of the UDF actually requires its children `ObjectInspector` to be the `ConstantObjectInspector`, which will cause exception.
e.g.
select named_struct("x", "str") from src limit 1;
I updated the method `wrap` by adding the one more parameter `ObjectInspector`(to describe what it expects to wrap to, for example: java.lang.Integer or IntWritable).
As well as the `unwrap` method by providing the input `ObjectInspector`.
Author: Cheng Hao <hao.cheng@intel.com>
Closes #2762 from chenghao-intel/udf_coi and squashes the following commits:
bcacfd7 [Cheng Hao] Shim for both Hive 0.12 & 0.13.1
2416e5d [Cheng Hao] revert to hive 0.12
5793c01 [Cheng Hao] add space before while
4e56e1b [Cheng Hao] style issue
683d3fd [Cheng Hao] Add golden files
fe591e4 [Cheng Hao] update HiveGenericUdf for set the ObjectInspector while constructing the DeferredObject
f6740fe [Cheng Hao] Support Constant ObjectInspector for Map & List
8814c3a [Cheng Hao] Passing ContantObjectInspector(when necessary) for UDF initializing
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Currently, `CTAS` (Create Table As Select) doesn't support specifying the `SerDe` in HQL. This PR will pass down the `ASTNode` into the physical operator `execution.CreateTableAsSelect`, which will extract the `CreateTableDesc` object via Hive `SemanticAnalyzer`. In the meantime, I also update the `HiveMetastoreCatalog.createTable` to optionally support the `CreateTableDesc` for table creation.
Author: Cheng Hao <hao.cheng@intel.com>
Closes #2570 from chenghao-intel/ctas_serde and squashes the following commits:
e011ef5 [Cheng Hao] shim for both 0.12 & 0.13.1
cfb3662 [Cheng Hao] revert to hive 0.12
c8a547d [Cheng Hao] Support SerDe properties within CTAS
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JIRA issue: [SPARK-3907]https://issues.apache.org/jira/browse/SPARK-3907
Add turncate table support
TRUNCATE TABLE table_name [PARTITION partition_spec];
partition_spec:
: (partition_col = partition_col_value, partition_col = partiton_col_value, ...)
Removes all rows from a table or partition(s). Currently target table should be native/managed table or exception will be thrown. User can specify partial partition_spec for truncating multiple partitions at once and omitting partition_spec will truncate all partitions in the table.
Author: wangxiaojing <u9jing@gmail.com>
Closes #2770 from wangxiaojing/spark-3907 and squashes the following commits:
63dbd81 [wangxiaojing] change hive scalastyle
7a03707 [wangxiaojing] add comment
f6e710e [wangxiaojing] change truncate table
a1f692c [wangxiaojing] Correct spelling mistakes
3b20007 [wangxiaojing] add truncate can not support column err message
e483547 [wangxiaojing] add golden file
77b1f20 [wangxiaojing] add truncate table support
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As part of the upgrade I also copy the newest version of the query tests, and whitelist a bunch of new ones that are now passing.
Author: Michael Armbrust <michael@databricks.com>
Closes #2936 from marmbrus/fix13tests and squashes the following commits:
d9cbdab [Michael Armbrust] Remove user specific tests
65801cd [Michael Armbrust] style and rat
8f6b09a [Michael Armbrust] Update test harness to work with both Hive 12 and 13.
f044843 [Michael Armbrust] Update Hive query tests and golden files to 0.13
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Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes #2344 from adrian-wang/date and squashes the following commits:
f15074a [Daoyuan Wang] remove outdated lines
2038085 [Daoyuan Wang] update return type
00fe81f [Daoyuan Wang] address lian cheng's comments
0df6ea1 [Daoyuan Wang] rebase and remove simple string
bb1b1ef [Daoyuan Wang] remove failing test
aa96735 [Daoyuan Wang] not cast for same type compare
30bf48b [Daoyuan Wang] resolve rebase conflict
617d1a8 [Daoyuan Wang] add date_udf case to white list
c37e848 [Daoyuan Wang] comment update
5429212 [Daoyuan Wang] change to long
f8f219f [Daoyuan Wang] revise according to Cheng Hao
0e0a4f5 [Daoyuan Wang] minor format
4ddcb92 [Daoyuan Wang] add java api for date
0e3110e [Daoyuan Wang] try to fix timezone issue
17fda35 [Daoyuan Wang] set test list
2dfbb5b [Daoyuan Wang] support date type
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PR #2226 was reverted because it broke Jenkins builds for unknown reason. This debugging PR aims to fix the Jenkins build.
This PR also fixes two bugs:
1. Compression configurations in `InsertIntoHiveTable` are disabled by mistake
The `FileSinkDesc` object passed to the writer container doesn't have compression related configurations. These configurations are not taken care of until `saveAsHiveFile` is called. This PR moves compression code forward, right after instantiation of the `FileSinkDesc` object.
1. `PreInsertionCasts` doesn't take table partitions into account
In `castChildOutput`, `table.attributes` only contains non-partition columns, thus for partitioned table `childOutputDataTypes` never equals to `tableOutputDataTypes`. This results funny analyzed plan like this:
```
== Analyzed Logical Plan ==
InsertIntoTable Map(partcol1 -> None, partcol2 -> None), false
MetastoreRelation default, dynamic_part_table, None
Project [c_0#1164,c_1#1165,c_2#1166]
Project [c_0#1164,c_1#1165,c_2#1166]
Project [c_0#1164,c_1#1165,c_2#1166]
... (repeats 99 times) ...
Project [c_0#1164,c_1#1165,c_2#1166]
Project [c_0#1164,c_1#1165,c_2#1166]
Project [1 AS c_0#1164,1 AS c_1#1165,1 AS c_2#1166]
Filter (key#1170 = 150)
MetastoreRelation default, src, None
```
Awful though this logical plan looks, it's harmless because all projects will be eliminated by optimizer. Guess that's why this issue hasn't been caught before.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Author: baishuo(白硕) <vc_java@hotmail.com>
Author: baishuo <vc_java@hotmail.com>
Closes #2616 from liancheng/dp-fix and squashes the following commits:
21935b6 [Cheng Lian] Adds back deleted trailing space
f471c4b [Cheng Lian] PreInsertionCasts should take table partitions into account
a132c80 [Cheng Lian] Fixes output compression
9c6eb2d [Cheng Lian] Adds tests to verify dynamic partitioning folder layout
0eed349 [Cheng Lian] Addresses @yhuai's comments
26632c3 [Cheng Lian] Adds more tests
9227181 [Cheng Lian] Minor refactoring
c47470e [Cheng Lian] Refactors InsertIntoHiveTable to a Command
6fb16d7 [Cheng Lian] Fixes typo in test name, regenerated golden answer files
d53daa5 [Cheng Lian] Refactors dynamic partitioning support
b821611 [baishuo] pass check style
997c990 [baishuo] use HiveConf.DEFAULTPARTITIONNAME to replace hive.exec.default.partition.name
761ecf2 [baishuo] modify according micheal's advice
207c6ac [baishuo] modify for some bad indentation
caea6fb [baishuo] modify code to pass scala style checks
b660e74 [baishuo] delete a empty else branch
cd822f0 [baishuo] do a little modify
8e7268c [baishuo] update file after test
3f91665 [baishuo(白硕)] Update Cast.scala
8ad173c [baishuo(白硕)] Update InsertIntoHiveTable.scala
051ba91 [baishuo(白硕)] Update Cast.scala
d452eb3 [baishuo(白硕)] Update HiveQuerySuite.scala
37c603b [baishuo(白硕)] Update InsertIntoHiveTable.scala
98cfb1f [baishuo(白硕)] Update HiveCompatibilitySuite.scala
6af73f4 [baishuo(白硕)] Update InsertIntoHiveTable.scala
adf02f1 [baishuo(白硕)] Update InsertIntoHiveTable.scala
1867e23 [baishuo(白硕)] Update SparkHadoopWriter.scala
6bb5880 [baishuo(白硕)] Update HiveQl.scala
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This reverts commit 0bbe7faeffa17577ae8a33dfcd8c4c783db5c909.
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a new PR base on new master. changes are the same as https://github.com/apache/spark/pull/1919
Author: baishuo(白硕) <vc_java@hotmail.com>
Author: baishuo <vc_java@hotmail.com>
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes #2226 from baishuo/patch-3007 and squashes the following commits:
e69ce88 [Cheng Lian] Adds tests to verify dynamic partitioning folder layout
b20a3dc [Cheng Lian] Addresses @yhuai's comments
096bbbc [baishuo(白硕)] Merge pull request #1 from liancheng/refactor-dp
1093c20 [Cheng Lian] Adds more tests
5004542 [Cheng Lian] Minor refactoring
fae9eff [Cheng Lian] Refactors InsertIntoHiveTable to a Command
528e84c [Cheng Lian] Fixes typo in test name, regenerated golden answer files
c464b26 [Cheng Lian] Refactors dynamic partitioning support
5033928 [baishuo] pass check style
2201c75 [baishuo] use HiveConf.DEFAULTPARTITIONNAME to replace hive.exec.default.partition.name
b47c9bf [baishuo] modify according micheal's advice
c3ab36d [baishuo] modify for some bad indentation
7ce2d9f [baishuo] modify code to pass scala style checks
37c1c43 [baishuo] delete a empty else branch
66e33fc [baishuo] do a little modify
88d0110 [baishuo] update file after test
a3961d9 [baishuo(白硕)] Update Cast.scala
f7467d0 [baishuo(白硕)] Update InsertIntoHiveTable.scala
c1a59dd [baishuo(白硕)] Update Cast.scala
0e18496 [baishuo(白硕)] Update HiveQuerySuite.scala
60f70aa [baishuo(白硕)] Update InsertIntoHiveTable.scala
0a50db9 [baishuo(白硕)] Update HiveCompatibilitySuite.scala
491c7d0 [baishuo(白硕)] Update InsertIntoHiveTable.scala
a2374a8 [baishuo(白硕)] Update InsertIntoHiveTable.scala
701a814 [baishuo(白硕)] Update SparkHadoopWriter.scala
dc24c41 [baishuo(白硕)] Update HiveQl.scala
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conversions
This is just another solution to SPARK-3485, in addition to PR #2355
In this patch, we will use ConventionHelper and FunctionRegistry to invoke a simple udf evaluation, which rely more on hive, but much cleaner and safer.
We can discuss which one is better.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes #2407 from adrian-wang/simpleudf and squashes the following commits:
15762d2 [Daoyuan Wang] add posmod test which would fail the test but now ok
0d69eb4 [Daoyuan Wang] another way to pass to hive simple udf
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This PR is based on #1883 authored by marmbrus. Key differences:
1. Batch pruning instead of partition pruning
When #1883 was authored, batched column buffer building (#1880) hadn't been introduced. This PR combines these two and provide partition batch level pruning, which leads to smaller memory footprints and can generally skip more elements. The cost is that the pruning predicates are evaluated more frequently (partition number multiplies batch number per partition).
1. More filters are supported
Filter predicates consist of `=`, `<`, `<=`, `>`, `>=` and their conjunctions and disjunctions are supported.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes #2188 from liancheng/in-mem-batch-pruning and squashes the following commits:
68cf019 [Cheng Lian] Marked sqlContext as @transient
4254f6c [Cheng Lian] Enables in-memory partition pruning in PartitionBatchPruningSuite
3784105 [Cheng Lian] Overrides InMemoryColumnarTableScan.sqlContext
d2a1d66 [Cheng Lian] Disables in-memory partition pruning by default
062c315 [Cheng Lian] HiveCompatibilitySuite code cleanup
16b77bf [Cheng Lian] Fixed pruning predication conjunctions and disjunctions
16195c5 [Cheng Lian] Enabled both disjunction and conjunction
89950d0 [Cheng Lian] Worked around Scala style check
9c167f6 [Cheng Lian] Minor code cleanup
3c4d5c7 [Cheng Lian] Minor code cleanup
ea59ee5 [Cheng Lian] Renamed PartitionSkippingSuite to PartitionBatchPruningSuite
fc517d0 [Cheng Lian] More test cases
1868c18 [Cheng Lian] Code cleanup, bugfix, and adding tests
cb76da4 [Cheng Lian] Added more predicate filters, fixed table scan stats for testing purposes
385474a [Cheng Lian] Merge branch 'inMemStats' into in-mem-batch-pruning
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`HiveCompatibilitySuite` already turns on in-memory columnar caching, it would be good to also enable compression to improve test coverage.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes #2190 from liancheng/compression-on and squashes the following commits:
88b536c [Cheng Lian] Code cleanup, narrowed field visibility
d13efd2 [Cheng Lian] Turns on in-memory columnar compression in HiveCompatibilitySuite
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udf_unix_timestamp format "yyyy MMM dd h:mm:ss a" run with not "America/Los_Angeles" TimeZone in HiveCompatibilitySuite
When run the udf_unix_timestamp of org.apache.spark.sql.hive.execution.HiveCompatibilitySuite testcase
with not "America/Los_Angeles" TimeZone throws error. [https://issues.apache.org/jira/browse/SPARK-3065]
add locale setting on beforeAll and afterAll method to fix the bug of HiveCompatibilitySuite testcase
Author: luogankun <luogankun@gmail.com>
Closes #1968 from luogankun/SPARK-3065 and squashes the following commits:
c167832 [luogankun] [SPARK-3065][SQL] Add Locale setting to HiveCompatibilitySuite
0a25e3a [luogankun] [SPARK-3065][SQL] Add Locale setting to HiveCompatibilitySuite
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(FROM|IN) table_name [(FROM|IN) db_name]" support
JIRA issue: [SPARK-3118] https://issues.apache.org/jira/browse/SPARK-3118
eg:
> SHOW TBLPROPERTIES test;
SHOW TBLPROPERTIES test;
numPartitions 0
numFiles 1
transient_lastDdlTime 1407923642
numRows 0
totalSize 82
rawDataSize 0
eg:
> SHOW COLUMNS in test;
SHOW COLUMNS in test;
OK
Time taken: 0.304 seconds
id
stid
bo
Author: u0jing <u9jing@gmail.com>
Closes #2034 from u0jing/spark-3118 and squashes the following commits:
b231d87 [u0jing] add golden answer files
35f4885 [u0jing] add 'show columns' and 'show tblproperties' support
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We can simple treat cross join as inner join without join conditions.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: adrian-wang <daoyuanwong@gmail.com>
Closes #2124 from adrian-wang/crossjoin and squashes the following commits:
8c9b7c5 [Daoyuan Wang] add a test
7d47bbb [adrian-wang] add cross join support for hql
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In spark sql component, the "show create table" syntax had been disabled.
We thought it is a useful funciton to describe a hive table.
Author: tianyi <tianyi@asiainfo-linkage.com>
Author: tianyi <tianyi@asiainfo.com>
Author: tianyi <tianyi.asiainfo@gmail.com>
Closes #1760 from tianyi/spark-2817 and squashes the following commits:
7d28b15 [tianyi] [SPARK-2817] fix too short prefix problem
cbffe8b [tianyi] [SPARK-2817] fix the case problem
565ec14 [tianyi] [SPARK-2817] fix the case problem
60d48a9 [tianyi] [SPARK-2817] use system temporary folder instead of temporary files in the source tree, and also clean some empty line
dbe1031 [tianyi] [SPARK-2817] move some code out of function rewritePaths, as it may be called multiple times
9b2ba11 [tianyi] [SPARK-2817] fix the line length problem
9f97586 [tianyi] [SPARK-2817] remove test.tmp.dir from pom.xml
bfc2999 [tianyi] [SPARK-2817] add "File.separator" support, create a "testTmpDir" outside the rewritePaths
bde800a [tianyi] [SPARK-2817] add "${system:test.tmp.dir}" support add "last_modified_by" to nonDeterministicLineIndicators in HiveComparisonTest
bb82726 [tianyi] [SPARK-2817] remove test which requires a system from the whitelist.
bbf6b42 [tianyi] [SPARK-2817] add a systemProperties named "test.tmp.dir" to pass the test which contains "${system:test.tmp.dir}"
a337bd6 [tianyi] [SPARK-2817] add "show create table" support
a03db77 [tianyi] [SPARK-2817] add "show create table" support
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1. there's no `hook_context.q` but a `hook_context_cs.q` in query folder
2. there's no `compute_stats_table.q` in query folder
3. there's no `having1.q` in query folder
4. `udf_E` and `udf_PI` appear twice in white list
Author: Daoyuan <daoyuan.wang@intel.com>
Closes #1634 from adrian-wang/testcases and squashes the following commits:
d7482ce [Daoyuan] change some test lists
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Hive Supports the operator "<=>", which returns same result with EQUAL(=) operator for non-null operands, but returns TRUE if both are NULL, FALSE if one of the them is NULL.
Author: Cheng Hao <hao.cheng@intel.com>
Closes #1570 from chenghao-intel/equalns and squashes the following commits:
8d6c789 [Cheng Hao] Remove the test case orc_predicate_pushdown
5b2ca88 [Cheng Hao] Add cases into whitelist
8e66cdd [Cheng Hao] Rename the EqualNSTo ==> EqualNullSafe
7af4b0b [Cheng Hao] Add EqualNS & Unit Tests
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Author: witgo <witgo@qq.com>
Closes #1403 from witgo/hive_compatibility and squashes the following commits:
4e5ecdb [witgo] The default does not run hive compatibility tests
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