Having two versions of the data type APIs (one for Java, one for Scala) requires downstream libraries to also have two versions of the APIs if the library wants to support both Java and Scala. I took a look at the Scala version of the data type APIs - it can actually work out pretty well for Java out of the box.
As part of the PR, I created a sql.types package and moved all type definitions there. I then removed the Java specific data type API along with a lot of the conversion code.
This subsumes https://github.com/apache/spark/pull/3925
Author: Reynold Xin <rxin@databricks.com>
Closes#3958 from rxin/SPARK-5123-datatype-2 and squashes the following commits:
66505cc [Reynold Xin] [SPARK-5123] Expose only one version of the data type APIs (i.e. remove the Java-specific API).
The pull only fixes the parsing error and changes API to use tableIdentifier. Joining different catalog datasource related change is not done in this pull.
Author: Alex Liu <alex_liu68@yahoo.com>
Closes#3941 from alexliu68/SPARK-SQL-4943-3 and squashes the following commits:
343ae27 [Alex Liu] [SPARK-4943][SQL] refactoring according to review
29e5e55 [Alex Liu] [SPARK-4943][SQL] fix failed Hive CTAS tests
6ae77ce [Alex Liu] [SPARK-4943][SQL] fix TestHive matching error
3652997 [Alex Liu] [SPARK-4943][SQL] Allow table name having dot to support db/catalog ...
This PR is a simplified version of several filter optimization rules introduced in #3778 authored by scwf. Newly introduced optimizations include:
1. `a && a` => `a`
2. `a || a` => `a`
3. `(a || b || c || ...) && (a || b || d || ...)` => `a && b && (c || d || ...)`
The 3rd rule is particularly useful for optimizing the following query, which is planned into a cartesian product
```sql
SELECT *
FROM t1, t2
WHERE (t1.key = t2.key AND t1.value > 10)
OR (t1.key = t2.key AND t2.value < 20)
```
to the following one, which is planned into an equi-join:
```sql
SELECT *
FROM t1, t2
WHERE t1.key = t2.key
AND (t1.value > 10 OR t2.value < 20)
```
The example above is quite artificial, but common predicates are likely to appear in real life complex queries (like the one mentioned in #3778).
A difference between this PR and #3778 is that these optimizations are not limited to `Filter`, but are generalized to all logical plan nodes. Thanks to scwf for bringing up these optimizations, and chenghao-intel for the generalization suggestion.
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Author: Cheng Lian <lian@databricks.com>
Closes#3784 from liancheng/normalize-filters and squashes the following commits:
caca560 [Cheng Lian] Moves filter normalization into BooleanSimplification rule
4ab3a58 [Cheng Lian] Fixes test failure, adds more tests
5d54349 [Cheng Lian] Fixes typo in comment
2abbf8e [Cheng Lian] Forgot our sacred Apache licence header...
cf95639 [Cheng Lian] Adds an optimization rule for filter normalization
case operator with decimal between different precision, we need change them to unlimited
Author: guowei2 <guowei2@asiainfo.com>
Closes#3767 from guowei2/SPARK-4928 and squashes the following commits:
c6a6e3e [guowei2] fix code style
3214e0a [guowei2] add test case
b4985a2 [guowei2] fix code style
27adf42 [guowei2] Fix: Operation '>,<,>=,<=' with Decimal report error
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#3616 from adrian-wang/sqrt and squashes the following commits:
d877439 [Daoyuan Wang] fix NULLTYPE
3effa2c [Daoyuan Wang] sqrt(negative value) should return null
This is a follow-up of SPARK-4593 (#3443).
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#3581 from ueshin/issues/SPARK-4720 and squashes the following commits:
c3959d4 [Takuya UESHIN] Make Remainder return null if the divider is 0.
Since `AttributeReference` resolution and `*` expansion are currently in separate rules, each pair requires a full iteration instead of being able to resolve in a single pass. Since its pretty easy to construct queries that have many of these in a row, I combine them into a single rule in this PR.
Author: Michael Armbrust <michael@databricks.com>
Closes#3674 from marmbrus/projectStars and squashes the following commits:
d83d6a1 [Michael Armbrust] Fix resolution of deeply nested Project(attr, Project(Star,...)).
Inserting data of type including `ArrayType.containsNull == false` or `MapType.valueContainsNull == false` or `StructType.fields.exists(_.nullable == false)` into Hive table will fail because `Cast` inserted by `HiveMetastoreCatalog.PreInsertionCasts` rule of `Analyzer` can't handle these types correctly.
Complex type cast rule proposal:
- Cast for non-complex types should be able to cast the same as before.
- Cast for `ArrayType` can evaluate if
- Element type can cast
- Nullability rule doesn't break
- Cast for `MapType` can evaluate if
- Key type can cast
- Nullability for casted key type is `false`
- Value type can cast
- Nullability rule for value type doesn't break
- Cast for `StructType` can evaluate if
- The field size is the same
- Each field can cast
- Nullability rule for each field doesn't break
- The nested structure should be the same.
Nullability rule:
- If the casted type is `nullable == true`, the target nullability should be `true`
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#3150 from ueshin/issues/SPARK-4293 and squashes the following commits:
e935939 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-4293
ba14003 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-4293
8999868 [Takuya UESHIN] Fix a test title.
f677c30 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-4293
287f410 [Takuya UESHIN] Add tests to insert data of types ArrayType / MapType / StructType with nullability is false into Hive table.
4f71bb8 [Takuya UESHIN] Make Cast be able to handle complex types.
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.
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
`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.
Add contains(key) to org.apache.spark.sql.catalyst.util.Metadata to test the existence of a key. Otherwise, Class Metadata's get methods may throw NoSuchElement exception if the key does not exist.
Testcases are added to MetadataSuite as well.
Author: kai <kaizeng@eecs.berkeley.edu>
Closes#3273 from kai-zeng/metadata-fix and squashes the following commits:
74b3d03 [kai] Added contains(key) to Metadata
This PR adds two features to the data sources API:
- Support for pushing down `IN` filters
- The ability for relations to optionally provide information about their `sizeInBytes`.
Author: Michael Armbrust <michael@databricks.com>
Closes#3260 from marmbrus/sourcesImprovements and squashes the following commits:
9a5e171 [Michael Armbrust] Use method instead of configuration directly
99c0e6b [Michael Armbrust] Add support for sizeInBytes.
416f167 [Michael Armbrust] Support for IN in data sources API.
2a04ab3 [Michael Armbrust] Simplify implementation of InSet.
Let's give this another go using a version of Hive that shades its JLine dependency.
Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Patrick Wendell <pwendell@gmail.com>
Closes#3159 from pwendell/scala-2.11-prashant and squashes the following commits:
e93aa3e [Patrick Wendell] Restoring -Phive-thriftserver profile and cleaning up build script.
f65d17d [Patrick Wendell] Fixing build issue due to merge conflict
a8c41eb [Patrick Wendell] Reverting dev/run-tests back to master state.
7a6eb18 [Patrick Wendell] Merge remote-tracking branch 'apache/master' into scala-2.11-prashant
583aa07 [Prashant Sharma] REVERT ME: removed hive thirftserver
3680e58 [Prashant Sharma] Revert "REVERT ME: Temporarily removing some Cli tests."
935fb47 [Prashant Sharma] Revert "Fixed by disabling a few tests temporarily."
925e90f [Prashant Sharma] Fixed by disabling a few tests temporarily.
2fffed3 [Prashant Sharma] Exclude groovy from sbt build, and also provide a way for such instances in future.
8bd4e40 [Prashant Sharma] Switched to gmaven plus, it fixes random failures observer with its predecessor gmaven.
5272ce5 [Prashant Sharma] SPARK_SCALA_VERSION related bugs.
2121071 [Patrick Wendell] Migrating version detection to PySpark
b1ed44d [Patrick Wendell] REVERT ME: Temporarily removing some Cli tests.
1743a73 [Patrick Wendell] Removing decimal test that doesn't work with Scala 2.11
f5cad4e [Patrick Wendell] Add Scala 2.11 docs
210d7e1 [Patrick Wendell] Revert "Testing new Hive version with shaded jline"
48518ce [Patrick Wendell] Remove association of Hive and Thriftserver profiles.
e9d0a06 [Patrick Wendell] Revert "Enable thritfserver for Scala 2.10 only"
67ec364 [Patrick Wendell] Guard building of thriftserver around Scala 2.10 check
8502c23 [Patrick Wendell] Enable thritfserver for Scala 2.10 only
e22b104 [Patrick Wendell] Small fix in pom file
ec402ab [Patrick Wendell] Various fixes
0be5a9d [Patrick Wendell] Testing new Hive version with shaded jline
4eaec65 [Prashant Sharma] Changed scripts to ignore target.
5167bea [Prashant Sharma] small correction
a4fcac6 [Prashant Sharma] Run against scala 2.11 on jenkins.
80285f4 [Prashant Sharma] MAven equivalent of setting spark.executor.extraClasspath during tests.
034b369 [Prashant Sharma] Setting test jars on executor classpath during tests from sbt.
d4874cb [Prashant Sharma] Fixed Python Runner suite. null check should be first case in scala 2.11.
6f50f13 [Prashant Sharma] Fixed build after rebasing with master. We should use ${scala.binary.version} instead of just 2.10
e56ca9d [Prashant Sharma] Print an error if build for 2.10 and 2.11 is spotted.
937c0b8 [Prashant Sharma] SCALA_VERSION -> SPARK_SCALA_VERSION
cb059b0 [Prashant Sharma] Code review
0476e5e [Prashant Sharma] Scala 2.11 support with repl and all build changes.
`Cast` from `DateType` to `DecimalType` throws `NullPointerException`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#3134 from ueshin/issues/SPARK-4270 and squashes the following commits:
7394e4b [Takuya UESHIN] Fix Cast from DateType to DecimalType.
This PR adds User-Defined Types (UDTs) to SQL. It is a precursor to using SchemaRDD as a Dataset for the new MLlib API. Currently, the UDT API is private since there is incomplete support (e.g., no Java or Python support yet).
Author: Joseph K. Bradley <joseph@databricks.com>
Author: Michael Armbrust <michael@databricks.com>
Author: Xiangrui Meng <meng@databricks.com>
Closes#3063 from marmbrus/udts and squashes the following commits:
7ccfc0d [Michael Armbrust] remove println
46a3aee [Michael Armbrust] Slightly easier to read test output.
6cc434d [Michael Armbrust] Recursively convert rows.
e369b91 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into udts
15c10a6 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into sql-udt2
f3c72fe [Joseph K. Bradley] Fixing merge
e13cd8a [Joseph K. Bradley] Removed Vector UDTs
5817b2b [Joseph K. Bradley] style edits
30ce5b2 [Joseph K. Bradley] updates based on code review
d063380 [Joseph K. Bradley] Cleaned up Java UDT Suite, and added warning about element ordering when creating schema from Java Bean
a571bb6 [Joseph K. Bradley] Removed old UDT code (registry and Java UDTs). Cleaned up other code. Extended JavaUserDefinedTypeSuite
6fddc1c [Joseph K. Bradley] Made MyLabeledPoint into a Java Bean
20630bc [Joseph K. Bradley] fixed scalastyle
fa86b20 [Joseph K. Bradley] Removed Java UserDefinedType, and made UDTs private[spark] for now
8de957c [Joseph K. Bradley] Modified UserDefinedType to store Java class of user type so that registerUDT takes only the udt argument.
8b242ea [Joseph K. Bradley] Fixed merge error after last merge. Note: Last merge commit also removed SQL UDT examples from mllib.
7f29656 [Joseph K. Bradley] Moved udt case to top of all matches. Small cleanups
b028675 [Xiangrui Meng] allow any type in UDT
4500d8a [Xiangrui Meng] update example code
87264a5 [Xiangrui Meng] remove debug code
3143ac3 [Xiangrui Meng] remove unnecessary changes
cfbc321 [Xiangrui Meng] support UDT in parquet
db16139 [Joseph K. Bradley] Added more doc for UserDefinedType. Removed unused code in Suite
759af7a [Joseph K. Bradley] Added more doc to UserDefineType
63626a4 [Joseph K. Bradley] Updated ScalaReflectionsSuite per @marmbrus suggestions
51e5282 [Joseph K. Bradley] fixed 1 test
f025035 [Joseph K. Bradley] Cleanups before PR. Added new tests
85872f6 [Michael Armbrust] Allow schema calculation to be lazy, but ensure its available on executors.
dff99d6 [Joseph K. Bradley] Added UDTs for Vectors in MLlib, plus DatasetExample using the UDTs
cd60cb4 [Joseph K. Bradley] Trying to get other SQL tests to run
34a5831 [Joseph K. Bradley] Added MLlib dependency on SQL.
e1f7b9c [Joseph K. Bradley] blah
2f40c02 [Joseph K. Bradley] renamed UDT types
3579035 [Joseph K. Bradley] udt annotation now working
b226b9e [Joseph K. Bradley] Changing UDT to annotation
fea04af [Joseph K. Bradley] more cleanups
964b32e [Joseph K. Bradley] some cleanups
893ee4c [Joseph K. Bradley] udt finallly working
50f9726 [Joseph K. Bradley] udts
04303c9 [Joseph K. Bradley] udts
39f8707 [Joseph K. Bradley] removed old udt suite
273ac96 [Joseph K. Bradley] basic UDT is working, but deserialization has yet to be done
8bebf24 [Joseph K. Bradley] commented out convertRowToScala for debugging
53de70f [Joseph K. Bradley] more udts...
982c035 [Joseph K. Bradley] still working on UDTs
19b2f60 [Joseph K. Bradley] still working on UDTs
0eaeb81 [Joseph K. Bradley] Still working on UDTs
105c5a3 [Joseph K. Bradley] Adding UserDefinedType to SQL, not done yet.
- Adds optional precision and scale to Spark SQL's decimal type, which behave similarly to those in Hive 13 (https://cwiki.apache.org/confluence/download/attachments/27362075/Hive_Decimal_Precision_Scale_Support.pdf)
- Replaces our internal representation of decimals with a Decimal class that can store small values in a mutable Long, saving memory in this situation and letting some operations happen directly on Longs
This is still marked WIP because there are a few TODOs, but I'll remove that tag when done.
Author: Matei Zaharia <matei@databricks.com>
Closes#2983 from mateiz/decimal-1 and squashes the following commits:
35e6b02 [Matei Zaharia] Fix issues after merge
227f24a [Matei Zaharia] Review comments
31f915e [Matei Zaharia] Implement Davies's suggestions in Python
eb84820 [Matei Zaharia] Support reading/writing decimals as fixed-length binary in Parquet
4dc6bae [Matei Zaharia] Fix decimal support in PySpark
d1d9d68 [Matei Zaharia] Fix compile error and test issues after rebase
b28933d [Matei Zaharia] Support decimal precision/scale in Hive metastore
2118c0d [Matei Zaharia] Some test and bug fixes
81db9cb [Matei Zaharia] Added mutable Decimal that will be more efficient for small precisions
7af0c3b [Matei Zaharia] Add optional precision and scale to DecimalType, but use Unlimited for now
ec0a947 [Matei Zaharia] Make the result of AVG on Decimals be Decimal, not Double
Add `metadata: Metadata` to `StructField` to store extra information of columns. `Metadata` is a simple wrapper over `Map[String, Any]` with value types restricted to Boolean, Long, Double, String, Metadata, and arrays of those types. SerDe is via JSON.
Metadata is preserved through simple operations like `SELECT`.
marmbrus liancheng
Author: Xiangrui Meng <meng@databricks.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#2701 from mengxr/structfield-metadata and squashes the following commits:
dedda56 [Xiangrui Meng] merge remote
5ef930a [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
c35203f [Xiangrui Meng] Merge pull request #1 from marmbrus/pr/2701
886b85c [Michael Armbrust] Expose Metadata and MetadataBuilder through the public scala and java packages.
589f314 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
1e2abcf [Xiangrui Meng] change default value of metadata to None in python
611d3c2 [Xiangrui Meng] move metadata from Expr to NamedExpr
ddfcfad [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
a438440 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
4266f4d [Xiangrui Meng] add StructField.toString back for backward compatibility
3f49aab [Xiangrui Meng] remove StructField.toString
24a9f80 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
473a7c5 [Xiangrui Meng] merge master
c9d7301 [Xiangrui Meng] organize imports
1fcbf13 [Xiangrui Meng] change metadata type in StructField for Scala/Java
60cc131 [Xiangrui Meng] add doc and header
60614c7 [Xiangrui Meng] add metadata
e42c452 [Xiangrui Meng] merge master
93518fb [Xiangrui Meng] support metadata in python
905bb89 [Xiangrui Meng] java conversions
618e349 [Xiangrui Meng] make tests work in scala
61b8e0f [Xiangrui Meng] merge master
7e5a322 [Xiangrui Meng] do not output metadata in StructField.toString
c41a664 [Xiangrui Meng] merge master
d8af0ed [Xiangrui Meng] move tests to SQLQuerySuite
67fdebb [Xiangrui Meng] add test on join
d65072e [Xiangrui Meng] remove Map.empty
367d237 [Xiangrui Meng] add test
c194d5e [Xiangrui Meng] add metadata field to StructField and Attribute
Add json and python api for date type.
By using Pickle, `java.sql.Date` was serialized as calendar, and recognized in python as `datetime.datetime`.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#2901 from adrian-wang/spark3988 and squashes the following commits:
c51a24d [Daoyuan Wang] convert datetime to date
5670626 [Daoyuan Wang] minor line combine
f760d8e [Daoyuan Wang] fix indent
444f100 [Daoyuan Wang] fix a typo
1d74448 [Daoyuan Wang] fix scala style
8d7dd22 [Daoyuan Wang] add json and python api for date type
Currently there is no support of Bitwise & , | in Spark HiveQl and Spark SQL as well. So this PR support the same.
I am closing https://github.com/apache/spark/pull/2926 as it has conflicts to merge. And also added support for Bitwise AND(&), OR(|) ,XOR(^), NOT(~) And I handled all review comments in that PR
Author: ravipesala <ravindra.pesala@huawei.com>
Closes#2961 from ravipesala/SPARK-3814-NEW4 and squashes the following commits:
a391c7a [ravipesala] Rebase with master
We cannot use EOL character like \n or \r in the operand of LIKE predicate.
So following condition is never true.
-- someStr is 'hoge\nfuga'
where someStr LIKE 'hoge_fuga'
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#2908 from sarutak/spark-sql-like-match-modification and squashes the following commits:
d15798b [Kousuke Saruta] Remove test setting for thriftserver
f99a2f4 [Kousuke Saruta] Fixed LIKE predicate so that we can use EOL character as in a operand
This patch adds Selenium tests for Spark's web UI. To avoid adding extra
dependencies to the test environment, the tests use Selenium's HtmlUnitDriver,
which is pure-Java, instead of, say, ChromeDriver.
I added new tests to try to reproduce a few UI bugs reported on JIRA, namely
SPARK-3021, SPARK-2105, and SPARK-2527. I wasn't able to reproduce these bugs;
I suspect that the older ones might have been fixed by other patches.
In order to use HtmlUnitDriver, I added an explicit dependency on the
org.apache.httpcomponents version of httpclient in order to prevent jets3t's
older version from taking precedence on the classpath.
I also upgraded ScalaTest to 2.2.1.
Author: Josh Rosen <joshrosen@apache.org>
Author: Josh Rosen <joshrosen@databricks.com>
Closes#2474 from JoshRosen/webui-selenium-tests and squashes the following commits:
fcc9e83 [Josh Rosen] scalautils -> scalactic package rename
510e54a [Josh Rosen] [SPARK-3616] Add basic Selenium tests to WebUISuite.
Previously cached data was found by `sameResult` plan matching on optimized plans. This technique however fails to locate the cached data when a temporary table with a projection is queried with a further reduced projection. The failure is due to the fact that optimization will collapse the projections, producing a plan that no longer produces the sameResult as the cached data (though the cached data still subsumes the desired data). For example consider the following previously failing test case.
```scala
sql("CACHE TABLE tempTable AS SELECT key FROM testData")
assertCached(sql("SELECT COUNT(*) FROM tempTable"))
```
In this PR I change the matching to occur after analysis instead of optimization, so that in the case of temporary tables, the plans will always match. I think this should work generally, however, this error does raise questions about the need to do more thorough subsumption checking when locating cached data.
Another question is what sort of semantics we want to provide when uncaching data from temporary tables. For example consider the following sequence of commands:
```scala
testData.select('key).registerTempTable("tempTable1")
testData.select('key).registerTempTable("tempTable2")
cacheTable("tempTable1")
// This obviously works.
assertCached(sql("SELECT COUNT(*) FROM tempTable1"))
// It seems good that this works ...
assertCached(sql("SELECT COUNT(*) FROM tempTable2"))
// ... but is this valid?
uncacheTable("tempTable2")
// Should this still be cached?
assertCached(sql("SELECT COUNT(*) FROM tempTable1"), 0)
```
Author: Michael Armbrust <michael@databricks.com>
Closes#2912 from marmbrus/cachingBug and squashes the following commits:
9c822d4 [Michael Armbrust] remove commented out code
5c72fb7 [Michael Armbrust] Add a test case / question about uncaching semantics.
63a23e4 [Michael Armbrust] Perform caching on analyzed instead of optimized plan.
03f1cfe [Michael Armbrust] Clean-up / add tests to SameResult suite.
Some developers want to replace `Optimizer` to fit their projects but can't do so because currently `Optimizer` is an `object`.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#2825 from ueshin/issues/SPARK-3969 and squashes the following commits:
abbc53c [Takuya UESHIN] Re-rename Optimizer object.
4d2e1bc [Takuya UESHIN] Rename Optimizer object.
9547a23 [Takuya UESHIN] Extract abstract class from Optimizer for developers to be able to replace Optimizer.
Package names of 2 test suites are different from their directory names.
- `GeneratedEvaluationSuite`
- `GeneratedMutableEvaluationSuite`
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#2835 from ueshin/issues/SPARK-3986 and squashes the following commits:
fa2cc05 [Takuya UESHIN] Fix package names to fit their directory names.
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
The In case class is replaced by a InSet class in case all the filters are literals, which uses a hashset instead of Sequence, thereby giving significant performance improvement (earlier the seq was using a worst case linear match (exists method) since expressions were assumed in the filter list) . Maximum improvement should be visible in case small percentage of large data matches the filter list.
Author: Yash Datta <Yash.Datta@guavus.com>
Closes#2561 from saucam/branch-1.1 and squashes the following commits:
4bf2d19 [Yash Datta] SPARK-3711: 1. Fix code style and import order 2. Fix optimization condition 3. Add tests for null in filter list 4. Add test case that optimization is not triggered in case of attributes in filter list
afedbcd [Yash Datta] SPARK-3711: 1. Add test cases for InSet class in ExpressionEvaluationSuite 2. Add class OptimizedInSuite on the lines of ConstantFoldingSuite, for the optimized In clause
0fc902f [Yash Datta] SPARK-3711: UnaryMinus will be handled by constantFolding
bd84c67 [Yash Datta] SPARK-3711: Incorporate review comments. Move optimization of In clause to Optimizer.scala by adding a rule. Add appropriate comments
430f5d1 [Yash Datta] SPARK-3711: Optimize the filter list in case of negative values as well
bee98aa [Yash Datta] SPARK-3711: Optimize where in clause filter queries
Calling `BinaryArithmetic.dataType` will throws exception until it's resolved, but in type coercion rule `Division`, seems doesn't follow this.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#2559 from chenghao-intel/type_coercion and squashes the following commits:
199a85d [Cheng Hao] Simplify the divide rule
dc55218 [Cheng Hao] fix bug of type coercion in div
Author: Renat Yusupov <re.yusupov@2gis.ru>
Closes#2641 from r3natko/feature/catalyst_option and squashes the following commits:
55d0c06 [Renat Yusupov] [SQL] SPARK-3776: Wrong conversion to Catalyst for Option[Product]
_Also addresses: SPARK-1671, SPARK-1379 and SPARK-3641_
This PR introduces a new trait, `CacheManger`, which replaces the previous temporary table based caching system. Instead of creating a temporary table that shadows an existing table with and equivalent cached representation, the cached manager maintains a separate list of logical plans and their cached data. After optimization, this list is searched for any matching plan fragments. When a matching plan fragment is found it is replaced with the cached data.
There are several advantages to this approach:
- Calling .cache() on a SchemaRDD now works as you would expect, and uses the more efficient columnar representation.
- Its now possible to provide a list of temporary tables, without having to decide if a given table is actually just a cached persistent table. (To be done in a follow-up PR)
- In some cases it is possible that cached data will be used, even if a cached table was not explicitly requested. This is because we now look at the logical structure instead of the table name.
- We now correctly invalidate when data is inserted into a hive table.
Author: Michael Armbrust <michael@databricks.com>
Closes#2501 from marmbrus/caching and squashes the following commits:
63fbc2c [Michael Armbrust] Merge remote-tracking branch 'origin/master' into caching.
0ea889e [Michael Armbrust] Address comments.
1e23287 [Michael Armbrust] Add support for cache invalidation for hive inserts.
65ed04a [Michael Armbrust] fix tests.
bdf9a3f [Michael Armbrust] Merge remote-tracking branch 'origin/master' into caching
b4b77f2 [Michael Armbrust] Address comments
6923c9d [Michael Armbrust] More comments / tests
80f26ac [Michael Armbrust] First draft of improved semantics for Spark SQL caching.
this patch fixes timestamp smaller than 0 and cast int as timestamp
select cast(1000 as timestamp) from src limit 1;
should return 1970-01-01 00:00:01, but we now take it as 1000 seconds.
also, current implementation has bug when the time is before 1970-01-01 00:00:00.
rxin marmbrus chenghao-intel
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#2458 from adrian-wang/timestamp and squashes the following commits:
4274b1d [Daoyuan Wang] set test not related to timezone
1234f66 [Daoyuan Wang] fix timestamp smaller than 0 and cast int as timestamp
Author: Cody Koeninger <cody.koeninger@mediacrossing.com>
Closes#2345 from koeninger/SPARK-3462 and squashes the following commits:
5c8d24d [Cody Koeninger] SPARK-3462 remove now-unused parameter
0788691 [Cody Koeninger] SPARK-3462 add tests, handle compatible schema with different aliases, per marmbrus feedback
ef47b3b [Cody Koeninger] SPARK-3462 push down filters and projections into Unions
LogicalPlan contains a ‘resolved’ attribute indicating that all of its execution requirements have been resolved. This attribute is not checked before query execution. The analyzer contains a step to check that all Expressions are resolved, but this is not equivalent to checking all LogicalPlans. In particular, the Union plan’s implementation of ‘resolved’ verifies that the types of its children’s columns are compatible. Because the analyzer does not check that a Union plan is resolved, it is possible to execute a Union plan that outputs different types in the same column. See SPARK-2781 for an example.
This patch adds two checks to the analyzer’s CheckResolution rule. First, each logical plan is checked to see if it is not resolved despite its children being resolved. This allows the ‘problem’ unresolved plan to be included in the TreeNodeException for reporting. Then as a backstop the root plan is checked to see if it is resolved, which recursively checks that the entire plan tree is resolved. Note that the resolved attribute is implemented recursively, and this patch also explicitly checks the resolved attribute on each logical plan in the tree. I assume the query plan trees will not be large enough for this redundant checking to meaningfully impact performance.
Because this patch starts validating that LogicalPlans are resolved before execution, I had to fix some cases where unresolved plans were passing through the analyzer as part of the implementation of the hive query system. In particular, HiveContext applies the CreateTables and PreInsertionCasts, and ExtractPythonUdfs rules manually after the analyzer runs. I moved these rules to the analyzer stage (for hive queries only), in the process completing a code TODO indicating the rules should be moved to the analyzer.
It’s worth noting that moving the CreateTables rule means introducing an analyzer rule with a significant side effect - in this case the side effect is creating a hive table. The rule will only attempt to create a table once even if its batch is executed multiple times, because it converts the InsertIntoCreatedTable plan it matches against into an InsertIntoTable. Additionally, these hive rules must be added to the Resolution batch rather than as a separate batch because hive rules rules may be needed to resolve non-root nodes, leaving the root to be resolved on a subsequent batch iteration. For example, the hive compatibility test auto_smb_mapjoin_14, and others, make use of a query plan where the root is a Union and its children are each a hive InsertIntoTable.
Mixing the custom hive rules with standard analyzer rules initially resulted in an additional failure because of policy differences between spark sql and hive when casting a boolean to a string. Hive casts booleans to strings as “true” / “false” while spark sql casts booleans to strings as “1” / “0” (causing the cast1.q test to fail). This behavior is a result of the BooleanCasts rule in HiveTypeCoercion.scala, and from looking at the implementation of BooleanCasts I think converting to to “1”/“0” is potentially a programming mistake. (If the BooleanCasts rule is disabled, casting produces “true”/“false” instead.) I believe “true” / “false” should be the behavior for spark sql - I changed the behavior so bools are converted to “true”/“false” to be consistent with hive, and none of the existing spark tests failed.
Finally, in some initial testing with hive it appears that an implicit type coercion of boolean to string results in a lowercase string, e.g. CONCAT( TRUE, “” ) -> “true” while an explicit cast produces an all caps string, e.g. CAST( TRUE AS STRING ) -> “TRUE”. The change I’ve made just converts to lowercase strings in all cases. I believe it is at least more correct than the existing spark sql implementation where all Cast expressions become “1” / “0”.
Author: Aaron Staple <aaron.staple@gmail.com>
Closes#1706 from staple/SPARK-2781 and squashes the following commits:
32683c4 [Aaron Staple] Fix compilation failure due to merge.
7c77fda [Aaron Staple] Move ExtractPythonUdfs to Analyzer's extendedRules in HiveContext.
d49bfb3 [Aaron Staple] Address review comments.
915b690 [Aaron Staple] Fix merge issue causing compilation failure.
701dcd2 [Aaron Staple] [SPARK-2781][SQL] Check resolution of LogicalPlans in Analyzer.
Type Coercion should support every type to have null value
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#2246 from adrian-wang/spark3363-0 and squashes the following commits:
c6241de [Daoyuan Wang] minor code clean
595b417 [Daoyuan Wang] Merge pull request #2 from marmbrus/pr/2246
832e640 [Michael Armbrust] reduce code duplication
ef6f986 [Daoyuan Wang] make double boolean miss in jsonRDD compatibleType
c619f0a [Daoyuan Wang] Type Coercion should support every type to have null value
Thus id property of the TreeNode API does save time in a faster way to compare 2 TreeNodes, it is kind of performance bottleneck during the expression object creation in a multi-threading env (because of the memory barrier).
Fortunately, the tree node comparison only happen once in master, so even we remove it, the entire performance will not be affected.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#2155 from chenghao-intel/treenode and squashes the following commits:
7cf2cd2 [Cheng Hao] Remove the implicit keyword for TreeNodeRef and some other small issues
5873415 [Cheng Hao] Remove the TreeNode.id
This PR adds a native implementation for SQL SQRT() and thus avoids delegating this function to Hive.
Author: William Benton <willb@redhat.com>
Closes#1750 from willb/spark-2813 and squashes the following commits:
22c8a79 [William Benton] Fixed missed newline from rebase
d673861 [William Benton] Added string coercions for SQRT and associated test case
e125df4 [William Benton] Added ExpressionEvaluationSuite test cases for SQRT
7b84bcd [William Benton] SQL SQRT now properly returns NULL for NULL inputs
8256971 [William Benton] added SQRT test to SqlQuerySuite
504d2e5 [William Benton] Added native SQRT implementation
It is common to want to describe sets of attributes that are in various parts of a query plan. However, the semantics of putting `AttributeReference` objects into a standard Scala `Set` result in subtle bugs when references differ cosmetically. For example, with case insensitive resolution it is possible to have two references to the same attribute whose names are not equal.
In this PR I introduce a new abstraction, an `AttributeSet`, which performs all comparisons using the globally unique `ExpressionId` instead of case class equality. (There is already a related class, [`AttributeMap`](https://github.com/marmbrus/spark/blob/inMemStats/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/AttributeMap.scala#L32)) This new type of set is used to fix a bug in the optimizer where needed attributes were getting projected away underneath join operators.
I also took this opportunity to refactor the expression and query plan base classes. In all but one instance the logic for computing the `references` of an `Expression` were the same. Thus, I moved this logic into the base class.
For query plans the semantics of the `references` method were ill defined (is it the references output? or is it those used by expression evaluation? or what?). As a result, this method wasn't really used very much. So, I removed it.
TODO:
- [x] Finish scala doc for `AttributeSet`
- [x] Scan the code for other instances of `Set[Attribute]` and refactor them.
- [x] Finish removing `references` from `QueryPlan`
Author: Michael Armbrust <michael@databricks.com>
Closes#2109 from marmbrus/attributeSets and squashes the following commits:
1c0dae5 [Michael Armbrust] work on serialization bug.
9ba868d [Michael Armbrust] Merge remote-tracking branch 'origin/master' into attributeSets
3ae5288 [Michael Armbrust] review comments
40ce7f6 [Michael Armbrust] style
d577cc7 [Michael Armbrust] Scaladoc
cae5d22 [Michael Armbrust] remove more references implementations
d6e16be [Michael Armbrust] Remove more instances of "def references" and normal sets of attributes.
fc26b49 [Michael Armbrust] Add AttributeSet class, remove references from Expression.
Make `ScalaReflection` be able to handle like:
- `Seq[Int]` as `ArrayType(IntegerType, containsNull = false)`
- `Seq[java.lang.Integer]` as `ArrayType(IntegerType, containsNull = true)`
- `Map[Int, Long]` as `MapType(IntegerType, LongType, valueContainsNull = false)`
- `Map[Int, java.lang.Long]` as `MapType(IntegerType, LongType, valueContainsNull = true)`
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1889 from ueshin/issues/SPARK-2969 and squashes the following commits:
24f1c5c [Takuya UESHIN] Change the default value of ArrayType.containsNull to true in Python API.
79f5b65 [Takuya UESHIN] Change the default value of ArrayType.containsNull to true in Java API.
7cd1a7a [Takuya UESHIN] Fix json test failures.
2cfb862 [Takuya UESHIN] Change the default value of ArrayType.containsNull to true.
2f38e61 [Takuya UESHIN] Revert the default value of MapTypes.valueContainsNull.
9fa02f5 [Takuya UESHIN] Fix a test failure.
1a9a96b [Takuya UESHIN] Modify ScalaReflection to handle ArrayType.containsNull and MapType.valueContainsNull.
Author: GuoQiang Li <witgo@qq.com>
Closes#1683 from witgo/SPARK-2766 and squashes the following commits:
d0db00c [GuoQiang Li] ScalaReflectionSuite throw an llegalArgumentException in JDK 6
The current PR contains the following changes:
* Expose `DataType`s in the sql package (internal details are private to sql).
* Users can create Rows.
* Introduce `applySchema` to create a `SchemaRDD` by applying a `schema: StructType` to an `RDD[Row]`.
* Add a function `simpleString` to every `DataType`. Also, the schema represented by a `StructType` can be visualized by `printSchema`.
* `ScalaReflection.typeOfObject` provides a way to infer the Catalyst data type based on an object. Also, we can compose `typeOfObject` with some custom logics to form a new function to infer the data type (for different use cases).
* `JsonRDD` has been refactored to use changes introduced by this PR.
* Add a field `containsNull` to `ArrayType`. So, we can explicitly mark if an `ArrayType` can contain null values. The default value of `containsNull` is `false`.
New APIs are introduced in the sql package object and SQLContext. You can find the scaladoc at
[sql package object](http://yhuai.github.io/site/api/scala/index.html#org.apache.spark.sql.package) and [SQLContext](http://yhuai.github.io/site/api/scala/index.html#org.apache.spark.sql.SQLContext).
An example of using `applySchema` is shown below.
```scala
import org.apache.spark.sql._
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
val schema =
StructType(
StructField("name", StringType, false) ::
StructField("age", IntegerType, true) :: Nil)
val people = sc.textFile("examples/src/main/resources/people.txt").map(_.split(",")).map(p => Row(p(0), p(1).trim.toInt))
val peopleSchemaRDD = sqlContext. applySchema(people, schema)
peopleSchemaRDD.printSchema
// root
// |-- name: string (nullable = false)
// |-- age: integer (nullable = true)
peopleSchemaRDD.registerAsTable("people")
sqlContext.sql("select name from people").collect.foreach(println)
```
I will add new contents to the SQL programming guide later.
JIRA: https://issues.apache.org/jira/browse/SPARK-2179
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1346 from yhuai/dataTypeAndSchema and squashes the following commits:
1d45977 [Yin Huai] Clean up.
a6e08b4 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
c712fbf [Yin Huai] Converts types of values based on defined schema.
4ceeb66 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
e5f8df5 [Yin Huai] Scaladoc.
122d1e7 [Yin Huai] Address comments.
03bfd95 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
2476ed0 [Yin Huai] Minor updates.
ab71f21 [Yin Huai] Format.
fc2bed1 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
bd40a33 [Yin Huai] Address comments.
991f860 [Yin Huai] Move "asJavaDataType" and "asScalaDataType" to DataTypeConversions.scala.
1cb35fe [Yin Huai] Add "valueContainsNull" to MapType.
3edb3ae [Yin Huai] Python doc.
692c0b9 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
1d93395 [Yin Huai] Python APIs.
246da96 [Yin Huai] Add java data type APIs to javadoc index.
1db9531 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
d48fc7b [Yin Huai] Minor updates.
33c4fec [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
b9f3071 [Yin Huai] Java API for applySchema.
1c9f33c [Yin Huai] Java APIs for DataTypes and Row.
624765c [Yin Huai] Tests for applySchema.
aa92e84 [Yin Huai] Update data type tests.
8da1a17 [Yin Huai] Add Row.fromSeq.
9c99bc0 [Yin Huai] Several minor updates.
1d9c13a [Yin Huai] Update applySchema API.
85e9b51 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
e495e4e [Yin Huai] More comments.
42d47a3 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
c3f4a02 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
2e58dbd [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
b8b7db4 [Yin Huai] 1. Move sql package object and package-info to sql-core. 2. Minor updates on APIs. 3. Update scala doc.
68525a2 [Yin Huai] Update JSON unit test.
3209108 [Yin Huai] Add unit tests.
dcaf22f [Yin Huai] Add a field containsNull to ArrayType to indicate if an array can contain null values or not. If an ArrayType is constructed by "ArrayType(elementType)" (the existing constructor), the value of containsNull is false.
9168b83 [Yin Huai] Update comments.
fc649d7 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
eca7d04 [Yin Huai] Add two apply methods which will be used to extract StructField(s) from a StructType.
949d6bb [Yin Huai] When creating a SchemaRDD for a JSON dataset, users can apply an existing schema.
7a6a7e5 [Yin Huai] Fix bug introduced by the change made on SQLContext.inferSchema.
43a45e1 [Yin Huai] Remove sql.util.package introduced in a previous commit.
0266761 [Yin Huai] Format
03eec4c [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
90460ac [Yin Huai] Infer the Catalyst data type from an object and cast a data value to the expected type.
3fa0df5 [Yin Huai] Provide easier ways to construct a StructType.
16be3e5 [Yin Huai] This commit contains three changes: * Expose `DataType`s in the sql package (internal details are private to sql). * Introduce `createSchemaRDD` to create a `SchemaRDD` from an `RDD` with a provided schema (represented by a `StructType`) and a provided function to construct `Row`, * Add a function `simpleString` to every `DataType`. Also, the schema represented by a `StructType` can be visualized by `printSchema`.
Adds a new method for evaluating expressions using code that is generated though Scala reflection. This functionality is configured by the SQLConf option `spark.sql.codegen` and is currently turned off by default.
Evaluation can be done in several specialized ways:
- *Projection* - Given an input row, produce a new row from a set of expressions that define each column in terms of the input row. This can either produce a new Row object or perform the projection in-place on an existing Row (MutableProjection).
- *Ordering* - Compares two rows based on a list of `SortOrder` expressions
- *Condition* - Returns `true` or `false` given an input row.
For each of the above operations there is both a Generated and Interpreted version. When generation for a given expression type is undefined, the code generator falls back on calling the `eval` function of the expression class. Even without custom code, there is still a potential speed up, as loops are unrolled and code can still be inlined by JIT.
This PR also contains a new type of Aggregation operator, `GeneratedAggregate`, that performs aggregation by using generated `Projection` code. Currently the required expression rewriting only works for simple aggregations like `SUM` and `COUNT`. This functionality will be extended in a future PR.
This PR also performs several clean ups that simplified the implementation:
- The notion of `Binding` all expressions in a tree automatically before query execution has been removed. Instead it is the responsibly of an operator to provide the input schema when creating one of the specialized evaluators defined above. In cases when the standard eval method is going to be called, binding can still be done manually using `BindReferences`. There are a few reasons for this change: First, there were many operators where it just didn't work before. For example, operators with more than one child, and operators like aggregation that do significant rewriting of the expression. Second, the semantics of equality with `BoundReferences` are broken. Specifically, we have had a few bugs where partitioning breaks because of the binding.
- A copy of the current `SQLContext` is automatically propagated to all `SparkPlan` nodes by the query planner. Before this was done ad-hoc for the nodes that needed this. However, this required a lot of boilerplate as one had to always remember to make it `transient` and also had to modify the `otherCopyArgs`.
Author: Michael Armbrust <michael@databricks.com>
Closes#993 from marmbrus/newCodeGen and squashes the following commits:
96ef82c [Michael Armbrust] Merge remote-tracking branch 'apache/master' into newCodeGen
f34122d [Michael Armbrust] Merge remote-tracking branch 'apache/master' into newCodeGen
67b1c48 [Michael Armbrust] Use conf variable in SQLConf object
4bdc42c [Michael Armbrust] Merge remote-tracking branch 'origin/master' into newCodeGen
41a40c9 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into newCodeGen
de22aac [Michael Armbrust] Merge remote-tracking branch 'origin/master' into newCodeGen
fed3634 [Michael Armbrust] Inspectors are not serializable.
ef8d42b [Michael Armbrust] comments
533fdfd [Michael Armbrust] More logging of expression rewriting for GeneratedAggregate.
3cd773e [Michael Armbrust] Allow codegen for Generate.
64b2ee1 [Michael Armbrust] Implement copy
3587460 [Michael Armbrust] Drop unused string builder function.
9cce346 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into newCodeGen
1a61293 [Michael Armbrust] Address review comments.
0672e8a [Michael Armbrust] Address comments.
1ec2d6e [Michael Armbrust] Address comments
033abc6 [Michael Armbrust] off by default
4771fab [Michael Armbrust] Docs, more test coverage.
d30fee2 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into newCodeGen
d2ad5c5 [Michael Armbrust] Refactor putting SQLContext into SparkPlan. Fix ordering, other test cases.
be2cd6b [Michael Armbrust] WIP: Remove old method for reference binding, more work on configuration.
bc88ecd [Michael Armbrust] Style
6cc97ca [Michael Armbrust] Merge remote-tracking branch 'origin/master' into newCodeGen
4220f1e [Michael Armbrust] Better config, docs, etc.
ca6cc6b [Michael Armbrust] WIP
9d67d85 [Michael Armbrust] Fix hive planner
fc522d5 [Michael Armbrust] Hook generated aggregation in to the planner.
e742640 [Michael Armbrust] Remove unneeded changes and code.
675e679 [Michael Armbrust] Upgrade paradise.
0093376 [Michael Armbrust] Comment / indenting cleanup.
d81f998 [Michael Armbrust] include schema for binding.
0e889e8 [Michael Armbrust] Use typeOf instead tq
f623ffd [Michael Armbrust] Quiet logging from test suite.
efad14f [Michael Armbrust] Remove some half finished functions.
92e74a4 [Michael Armbrust] add overrides
a2b5408 [Michael Armbrust] WIP: Code generation with scala reflection.
Author: Michael Armbrust <michael@databricks.com>
Closes#1557 from marmbrus/fixDivision and squashes the following commits:
b85077f [Michael Armbrust] Fix unit tests.
af98f29 [Michael Armbrust] Change DIV to long type
0c29ae8 [Michael Armbrust] Fix division semantics for hive
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
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#1491 from ueshin/issues/SPARK-2588 and squashes the following commits:
43d0a46 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-2588
1023ea0 [Takuya UESHIN] Modify tests to use DSLs.
2310bf1 [Takuya UESHIN] Add some more DSLs.
