Currently, we use o.a.s.sql.Row both internally and externally. The external interface is wider than what the internal needs because it is designed to facilitate end-user programming. This design has proven to be very error prone and cumbersome for internal Row implementations.
As a first step, we create an InternalRow interface in the catalyst module, which is identical to the current Row interface. And we switch all internal operators/expressions to use this InternalRow instead. When we need to expose Row, we convert the InternalRow implementation into Row for users.
For all public API, we use Row (for example, data source APIs), which will be converted into/from InternalRow by CatalystTypeConverters.
For all internal data sources (Json, Parquet, JDBC, Hive), we use InternalRow for better performance, casted into Row in buildScan() (without change the public API). When create a PhysicalRDD, we cast them back to InternalRow.
cc rxin marmbrus JoshRosen
Author: Davies Liu <davies@databricks.com>
Closes#6792 from davies/internal_row and squashes the following commits:
f2abd13 [Davies Liu] fix scalastyle
a7e025c [Davies Liu] move InternalRow into catalyst
30db8ba [Davies Liu] Merge branch 'master' of github.com:apache/spark into internal_row
7cbced8 [Davies Liu] separate Row and InternalRow
MLUtils.appendBias method is heavily used in creating intercepts for linear models.
This method uses Breeze's vector concatenation which is very slow compared to the plain
System.arrayCopy. This improvement is to change the implementation to use System.arrayCopy.
I saw the following performance improvements after the change:
Benchmark with mnist dataset for 50 times:
MLUtils.appendBias (SparseVector Before): 47320 ms
MLUtils.appendBias (SparseVector After): 1935 ms
MLUtils.appendBias (DenseVector Before): 5340 ms
MLUtils.appendBias (DenseVector After): 4080 ms
This is almost a 24 times performance boost for SparseVectors.
Author: Roger Menezes <rmenezes@netflix.com>
Closes#6768 from rogermenezes/improve-append-bias and squashes the following commits:
4e42f75 [Roger Menezes] address feedback
e999d79 [Roger Menezes] first commit
- Kinesis API updated
- Kafka version updated, and Python API for Direct Kafka added
- Added SQLContext.getOrCreate()
- Added information on how to get partitionId in foreachRDD
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#6781 from tdas/SPARK-7284 and squashes the following commits:
aac7be0 [Tathagata Das] Added information on how to get partition id
a66ec22 [Tathagata Das] Complete the line incomplete line,
a92ca39 [Tathagata Das] Updated streaming documentation
Safeguard against DOM rewriting.
Author: Andrew Or <andrew@databricks.com>
Closes#6787 from andrewor14/dag-viz-trim and squashes the following commits:
0fb4afe [Andrew Or] Trim input metadata from DOM
… SPARK_TACHYON_MAP
This contribution is my original work and I license the work to the project under the project's open source license.
Author: Mark Smith <mark.smith@bronto.com>
Closes#6776 from markmsmith/SPARK-8322 and squashes the following commits:
d744244 [Mark Smith] [SPARK-8322][EC2] Fixed tachyon mapp entry to point to 0.6.4
e4f14d3 [Mark Smith] [SPARK-8322][EC2] Added spark 1.4.0 into the VALID_SPARK_VERSIONS and SPARK_TACHYON_MAP
It's a follow up of https://github.com/apache/spark/pull/6173, for expressions like `Coalesce` that have a `Seq[Expression]`, when we do semantic equal check for it, we need to do semantic equal check for all of its children.
Also we can just use `Seq[(Expression, NamedExpression)]` instead of `Map[Expression, NamedExpression]` as we only search it with `find`.
chenghao-intel, I agree that we probably never knows `semanticEquals` in a general way, but I think we have done that in `TreeNode`, so we can use similar logic. Then we can handle something like `Coalesce(children: Seq[Expression])` correctly.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#6261 from cloud-fan/tmp and squashes the following commits:
4daef88 [Wenchen Fan] address comments
dd8fbd9 [Wenchen Fan] correct semanticEquals
This brings in major improvement in that footers are not read on the driver. This also cleans up the code in parquetTableOperations, where we had to override getSplits to eliminate multiple listStatus calls.
cc liancheng
are there any other changes we need for this ?
Author: Yash Datta <Yash.Datta@guavus.com>
Closes#5889 from saucam/parquet_1.6 and squashes the following commits:
d1bf41e [Yash Datta] SPARK-7340: Fix scalastyle and incorporate review comments
c9aa042 [Yash Datta] SPARK-7340: Use the new user defined filter predicate for pushing down inset into parquet
56bc750 [Yash Datta] SPARK-7340: Change parquet version to latest release
[Related PR SPARK-7044] (https://github.com/apache/spark/pull/5671)
Author: zhichao.li <zhichao.li@intel.com>
Closes#6404 from zhichao-li/transform and squashes the following commits:
8418c97 [zhichao.li] add comments and remove useless failAfter logic
d9677e1 [zhichao.li] redirect the error desitination to be the same as the current process
In some cases, Spark SQL pushes sorting operations into the shuffle layer by specifying a key ordering as part of the shuffle dependency. I think that we should not do this:
- Since we do not delegate aggregation to Spark's shuffle, specifying the keyOrdering as part of the shuffle has no effect on the shuffle map side.
- By performing the shuffle ourselves (by inserting a sort operator after the shuffle instead), we can use the Exchange planner to choose specialized sorting implementations based on the types of rows being sorted.
- We can remove some complexity from SqlSerializer2 by not requiring it to know about sort orderings, since SQL's own sort operators will already perform the necessary defensive copying.
This patch removes Exchange's `canSortWithShuffle` path and the associated code in `SqlSerializer2`. Shuffles that used to go through the `canSortWithShuffle` path would always wind up using Spark's `ExternalSorter` (inside of `HashShuffleReader`); to avoid a performance regression as a result of handling these shuffles ourselves, I've changed the SQLConf defaults so that external sorting is enabled by default.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#6772 from JoshRosen/SPARK-8317 and squashes the following commits:
ebf9c0f [Josh Rosen] Do not push sort into shuffle in Exchange operator
bf3b4c8 [Josh Rosen] Enable external sort by default
When df.cache() method called, the `withCachedData` of `QueryExecution` has been created, which mean it will not look up the cached tables when action method called afterward.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#5714 from chenghao-intel/SPARK-7158 and squashes the following commits:
58ea8aa [Cheng Hao] style issue
2bf740f [Cheng Hao] create new QueryExecution instance for CacheManager
a5647d9 [Cheng Hao] hide the queryExecution of DataFrame
fbfd3c5 [Cheng Hao] make the DataFrame.queryExecution mutable for cache/persist/unpersist
Unit test is still in Scala.
Author: Reynold Xin <rxin@databricks.com>
Closes#6738 from rxin/utf8string-java and squashes the following commits:
562dc6e [Reynold Xin] Flag...
98e600b [Reynold Xin] Another try with encoding setting ..
cfa6bdf [Reynold Xin] Merge branch 'master' into utf8string-java
a3b124d [Reynold Xin] Try different UTF-8 encoded characters.
1ff7c82 [Reynold Xin] Enable UTF-8 encoding.
82d58cc [Reynold Xin] Reset run-tests.
2cb3c69 [Reynold Xin] Use utf-8 encoding in set bytes.
53f8ef4 [Reynold Xin] Hack Jenkins to run one test.
9a48e8d [Reynold Xin] Fixed runtime compilation error.
911c450 [Reynold Xin] Moved unit test also to Java.
4eff7bd [Reynold Xin] Improved unit test coverage.
8e89a3c [Reynold Xin] Fixed tests.
77c64bd [Reynold Xin] Fixed string type codegen.
ffedb62 [Reynold Xin] Code review feedback.
0967ce6 [Reynold Xin] Fixed import ordering.
45a123d [Reynold Xin] [SPARK-8286] Rewrite UTF8String in Java and move it into unsafe package.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#6766 from vanzin/SPARK-6511 and squashes the following commits:
49f0f67 [Marcelo Vanzin] [SPARK-6511] [docs] Fix example command in hadoop-provided docs.
```
create table t1 (a int, b string) as select key, value from src;
desc t1;
key int NULL
value string NULL
```
Thus Hive doesn't support specifying the column list for target table in CTAS, however, we should either throwing exception explicity, or supporting the this feature, we just pick up the later one, which seems useful and straightforward.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#6458 from chenghao-intel/ctas_column and squashes the following commits:
d1fa9b6 [Cheng Hao] bug in unittest
4e701aa [Cheng Hao] update as feedback
f305ec1 [Cheng Hao] support specifying the column list for target table in CTAS
Will send another PR for `branch-1.4`
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#6764 from shivaram/SPARK-8310 and squashes the following commits:
d8cd3b3 [Shivaram Venkataraman] This updates the master branch EC2 versions
This PR fix a few small issues about codgen:
1. cast decimal to boolean
2. do not inline literal with null
3. improve SpecificRow.equals()
4. test expressions with optimized express
5. fix compare with BinaryType
cc rxin chenghao-intel
Author: Davies Liu <davies@databricks.com>
Closes#6755 from davies/fix_codegen and squashes the following commits:
ef27343 [Davies Liu] address comments
6617ea6 [Davies Liu] fix scala tyle
70b7dda [Davies Liu] improve codegen
Spark SQL does not support timezone, and Pyrolite does not support timezone well. This patch will convert datetime into POSIX timestamp (without confusing of timezone), which is used by SQL. If the datetime object does not have timezone, it's treated as local time.
The timezone in RDD will be lost after one round trip, all the datetime from SQL will be local time.
Because of Pyrolite, datetime from SQL only has precision as 1 millisecond.
This PR also drop the timezone in date, convert it to number of days since epoch (used in SQL).
Author: Davies Liu <davies@databricks.com>
Closes#6250 from davies/tzone and squashes the following commits:
44d8497 [Davies Liu] add timezone support for DateType
99d9d9c [Davies Liu] use int for timestamp
10aa7ca [Davies Liu] Merge branch 'master' of github.com:apache/spark into tzone
6a29aa4 [Davies Liu] support datetime with timezone
This change is a simple one and specifies a stack size of 4096k instead of the vendor default for Java tests (the defaults vary between Java vendors). This remedies test failures observed with JavaALSSuite with IBM and Oracle Java owing to a lower default size in comparison to the size with OpenJDK. 4096k is a suitable default where the tests pass with each Java vendor tested. The alternative is to reduce the number of iterations in the test (no observed failures with 5 iterations instead of 15).
-Xss works with Oracle's HotSpot VM, IBM's J9 VM and OpenJDK (IcedTea).
I have ensured this does not have any negative implications for other tests.
Author: Adam Roberts <aroberts@uk.ibm.com>
Author: a-roberts <aroberts@uk.ibm.com>
Closes#6727 from a-roberts/IncJavaStackSize and squashes the following commits:
ab40aea [Adam Roberts] Specify stack size for SBT builds
5032d8d [a-roberts] Update pom.xml
Author: Daoyuan Wang <daoyuan.wang@intel.com>
This patch had conflicts when merged, resolved by
Committer: Reynold Xin <rxin@databricks.com>
Closes#6718 from adrian-wang/udflog2 and squashes the following commits:
3909f48 [Daoyuan Wang] math function: log2
Author: Cheng Hao <hao.cheng@intel.com>
Closes#6724 from chenghao-intel/length and squashes the following commits:
aaa3c31 [Cheng Hao] revert the additional change
97148a9 [Cheng Hao] remove the codegen testing temporally
ae08003 [Cheng Hao] update the comments
1eb1fd1 [Cheng Hao] simplify the code as commented
3e92d32 [Cheng Hao] use the selectExpr in unit test intead of SQLQuery
3c729aa [Cheng Hao] fix bug for constant null value in codegen
3641f06 [Cheng Hao] keep the length() method for registered function
8e30171 [Cheng Hao] update the code as comment
db604ae [Cheng Hao] Add code gen support
548d2ef [Cheng Hao] register the length()
09a0738 [Cheng Hao] add length support
Currently we only support `Seq[Expression]`, we should handle cases like `Seq[Seq[Expression]]` so that we can remove the unnecessary `GroupExpression`.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#6706 from cloud-fan/clean and squashes the following commits:
60a1193 [Wenchen Fan] support nested expression sequence and remove GroupExpression
case cs CombineSum(expr) =>
val calcType = expr.dataType
expr.dataType match {
case DecimalType.Fixed(_, _) =>
DecimalType.Unlimited
case _ =>
expr.dataType
}
calcType is always expr.dataType. credits are all belong to IntelliJ
Author: navis.ryu <navis@apache.org>
Closes#6736 from navis/SPARK-8285 and squashes the following commits:
20382c1 [navis.ryu] [SPARK-8285] [SQL] CombineSum should be calculated as unlimited decimal first
This PR change to use Long as internal type for TimestampType for efficiency, which means it will the precision below 100ns.
Author: Davies Liu <davies@databricks.com>
Closes#6733 from davies/timestamp and squashes the following commits:
d9565fa [Davies Liu] remove print
65cf2f1 [Davies Liu] fix Timestamp in SparkR
86fecfb [Davies Liu] disable two timestamp tests
8f77ee0 [Davies Liu] fix scala style
246ee74 [Davies Liu] address comments
309d2e1 [Davies Liu] use Long for TimestampType in SQL
Test cases for both StreamingLinearRegression and StreamingLogisticRegression, and code fix.
Edit:
This contribution is my original work and I license the work to the project under the project's open source license.
Author: Paavo <pparkkin@gmail.com>
Closes#6713 from pparkkin/streamingmodel-empty-rdd and squashes the following commits:
ff5cd78 [Paavo] Update strings to use interpolation.
db234cf [Paavo] Use !rdd.isEmpty.
54ad89e [Paavo] Test case for empty stream.
393e36f [Paavo] Ignore empty RDDs.
0bfc365 [Paavo] Test case for empty stream.
Set preferred locations for reduce tasks.
The basic design is that we maintain a map from reducerId to a list of (sizes, locations) for each
shuffle. We then set the preferred locations to be any machines that have 20% of more of the output
that needs to be read by the reduce task. This will result in at most 5 preferred locations for
each reduce task.
Selecting the preferred locations involves O(# map tasks * # reduce tasks) computation, so we
restrict this feature to cases where we have fewer than 1000 map tasks and 1000 reduce tasks.
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#6652 from shivaram/reduce-locations and squashes the following commits:
492e25e [Shivaram Venkataraman] Remove unused import
2ef2d39 [Shivaram Venkataraman] Address code review comments
897a914 [Shivaram Venkataraman] Remove unused hash map
f5be578 [Shivaram Venkataraman] Use fraction of map outputs to determine locations Also removes caching of preferred locations to make the API cleaner
68bc29e [Shivaram Venkataraman] Fix line length
1090b58 [Shivaram Venkataraman] Change flag name
77ce7d8 [Shivaram Venkataraman] Merge branch 'master' of https://github.com/apache/spark into reduce-locations
e5d56bd [Shivaram Venkataraman] Add flag to turn off locality for shuffle deps
6cfae98 [Shivaram Venkataraman] Filter out zero blocks, rename variables
9d5831a [Shivaram Venkataraman] Address some more comments
8e31266 [Shivaram Venkataraman] Fix style
0df3180 [Shivaram Venkataraman] Address code review comments
e7d5449 [Shivaram Venkataraman] Fix merge issues
ad7cb53 [Shivaram Venkataraman] Merge branch 'master' of https://github.com/apache/spark into reduce-locations
df14cee [Shivaram Venkataraman] Merge branch 'master' of https://github.com/apache/spark into reduce-locations
5093aea [Shivaram Venkataraman] Merge branch 'master' of https://github.com/apache/spark into reduce-locations
0171d3c [Shivaram Venkataraman] Merge branch 'master' of https://github.com/apache/spark into reduce-locations
bc4dfd6 [Shivaram Venkataraman] Merge branch 'master' of https://github.com/apache/spark into reduce-locations
774751b [Shivaram Venkataraman] Fix bug introduced by line length adjustment
34d0283 [Shivaram Venkataraman] Fix style issues
3b464b7 [Shivaram Venkataraman] Set preferred locations for reduce tasks This is another attempt at #1697 addressing some of the earlier concerns. This adds a couple of thresholds based on number map and reduce tasks beyond which we don't use preferred locations for reduce tasks.
SPARK_JAVA_OPTS was missed in reconstructing the launcher part, we should add it back so process launched by spark-class could read it properly. And so does `SPARK_DRIVER_MEMORY`.
The missing part is [here](1c30afdf94/bin/spark-class (L97)).
Author: WangTaoTheTonic <wangtao111@huawei.com>
Author: Tao Wang <wangtao111@huawei.com>
Closes#6741 from WangTaoTheTonic/SPARK-8290 and squashes the following commits:
bd89f0f [Tao Wang] make sure the memory setting is right too
e313520 [WangTaoTheTonic] spark class command builder need read SPARK_JAVA_OPTS
1. Add `log4j-defaults-repl.properties` that has log level WARN.
2. When logging is initialized, check whether inside the REPL. If so, use `log4j-defaults-repl.properties`.
3. Print the following information if using `log4j-defaults-repl.properties`:
```
Using Spark's repl log4j profile: org/apache/spark/log4j-defaults-repl.properties
To adjust logging level use sc.setLogLevel("INFO")
```
Author: zsxwing <zsxwing@gmail.com>
Closes#6734 from zsxwing/log4j-repl and squashes the following commits:
3835eff [zsxwing] Change default log level to WARN in the REPL
The root cause of SPARK-7527 is `createNullValue` returns an incompatible value `Byte(0)` for `char` and `boolean`.
This PR fixes it and corrects the class name of the main class, and also adds an unit test to demonstrate it.
Author: zsxwing <zsxwing@gmail.com>
Closes#6735 from zsxwing/SPARK-7527 and squashes the following commits:
bbdb271 [zsxwing] Use pattern match in createNullValue
b0a0e7e [zsxwing] Remove the noisy in the test output
903e269 [zsxwing] Remove the code for Utils.isInInterpreter == false
5f92dc1 [zsxwing] Fix createNullValue to return the correct null values and REPL mode detection
IBM Java has an extra method when we do getStackTrace(): this is "getStackTraceImpl", a native method. This causes two tests to fail within "DStreamScopeSuite" when running with IBM Java. Instead of "map" or "filter" being the method names found, "getStackTrace" is returned. This commit addresses such an issue by using dropWhile. Given that our current method is withScope, we look for the next method that isn't ours: we don't care about methods that come before us in the stack trace: e.g. getStackTrace (regardless of how many levels this might go).
IBM:
java.lang.Thread.getStackTraceImpl(Native Method)
java.lang.Thread.getStackTrace(Thread.java:1117)
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:104)
Oracle:
PRINTING STACKTRACE!!!
java.lang.Thread.getStackTrace(Thread.java:1552)
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:106)
I've tested this with Oracle and IBM Java, no side effects for other tests introduced.
Author: Adam Roberts <aroberts@uk.ibm.com>
Author: a-roberts <aroberts@uk.ibm.com>
Closes#6740 from a-roberts/RDDScopeStackCrawlFix and squashes the following commits:
13ce390 [Adam Roberts] Ensure consistency with String equality checking
a4fc0e0 [a-roberts] Update RDDOperationScope.scala
Read number of threads for RBackend from configuration.
[SPARK-8282] #comment Linking with JIRA
Author: Hossein <hossein@databricks.com>
Closes#6730 from falaki/SPARK-8282 and squashes the following commits:
33b3d98 [Hossein] Documented new config parameter
70f2a9c [Hossein] Fixing import
ec44225 [Hossein] Read number of threads for RBackend from configuration
The bug description is a little misleading: the actual issue is that
.py files are not handled correctly when distributed by YARN. They're
added to "spark.submit.pyFiles", which, when processed by context.py,
explicitly whitelists certain extensions (see PACKAGE_EXTENSIONS),
and that does not include .py files.
On top of that, archives were not handled at all! They made it to the
driver's python path, but never made it to executors, since the mechanism
used to propagate their location (spark.submit.pyFiles) only works on
the driver side.
So, instead, ignore "spark.submit.pyFiles" and just build PYTHONPATH
correctly for both driver and executors. Individual .py files are
placed in a subdirectory of the container's local dir in the cluster,
which is then added to the python path. Archives are added directly.
The change, as a side effect, ends up solving the symptom described
in the bug. The issue was not that the files were not being distributed,
but that they were never made visible to the python application
running under Spark.
Also included is a proper unit test for running python on YARN, which
broke in several different ways with the previous code.
A short walk around of the changes:
- SparkSubmit does not try to be smart about how YARN handles python
files anymore. It just passes down the configs to the YARN client
code.
- The YARN client distributes python files and archives differently,
placing the files in a subdirectory.
- The YARN client now sets PYTHONPATH for the processes it launches;
to properly handle different locations, it uses YARN's support for
embedding env variables, so to avoid YARN expanding those at the
wrong time, SparkConf is now propagated to the AM using a conf file
instead of command line options.
- Because the Client initialization code is a maze of implicit
dependencies, some code needed to be moved around to make sure
all needed state was available when the code ran.
- The pyspark tests in YarnClusterSuite now actually distribute and try
to use both a python file and an archive containing a different python
module. Also added a yarn-client tests for completeness.
- I cleaned up some of the code around distributing files to YARN, to
avoid adding more copied & pasted code to handle the new files being
distributed.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#6360 from vanzin/SPARK-5479 and squashes the following commits:
bcaf7e6 [Marcelo Vanzin] Feedback.
c47501f [Marcelo Vanzin] Fix yarn-client mode.
46b1d0c [Marcelo Vanzin] Merge branch 'master' into SPARK-5479
c743778 [Marcelo Vanzin] Only pyspark cares about python archives.
c8e5a82 [Marcelo Vanzin] Actually run pyspark in client mode.
705571d [Marcelo Vanzin] Move some code to the YARN module.
1dd4d0c [Marcelo Vanzin] Review feedback.
71ee736 [Marcelo Vanzin] Merge branch 'master' into SPARK-5479
220358b [Marcelo Vanzin] Scalastyle.
cdbb990 [Marcelo Vanzin] Merge branch 'master' into SPARK-5479
7fe3cd4 [Marcelo Vanzin] No need to distribute primary file to executors.
09045f1 [Marcelo Vanzin] Style.
943cbf4 [Marcelo Vanzin] [SPARK-5479] [yarn] Handle --py-files correctly in YARN.
Author: Cheng Lian <lian@databricks.com>
Closes#6749 from liancheng/java-sample-fix and squashes the following commits:
5b44585 [Cheng Lian] Fixes a minor Java example error in SQL programming guide
Changed ```SparkEnv.actorSystem``` to be a function such that we can use the deprecated flag with it and added a deprecated message.
Author: Ilya Ganelin <ilya.ganelin@capitalone.com>
Closes#6731 from ilganeli/SPARK-7996 and squashes the following commits:
be43817 [Ilya Ganelin] Restored to val
9ed89e7 [Ilya Ganelin] Added a version info for deprecation
9610b08 [Ilya Ganelin] Converted actorSystem to function and added deprecated flag
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#6716 from adrian-wang/epi and squashes the following commits:
e2e8dbd [Daoyuan Wang] move tests
11b351c [Daoyuan Wang] add tests and remove pu
db331c9 [Daoyuan Wang] py style
599ddd8 [Daoyuan Wang] add py
e6783ef [Daoyuan Wang] register function
82d426e [Daoyuan Wang] add function entry
dbf3ab5 [Daoyuan Wang] add PI and E
This is a followup to #6712.
Author: Reynold Xin <rxin@databricks.com>
Closes#6739 from rxin/6712-followup and squashes the following commits:
fd9acfb [Reynold Xin] [SPARK-7886] Added unit test for HAVING aggregate pushdown.
This builds on #6710 and also uses FunctionRegistry for function lookup in HiveContext.
Author: Reynold Xin <rxin@databricks.com>
Closes#6712 from rxin/udf-registry-hive and squashes the following commits:
f4c2df0 [Reynold Xin] Fixed style violation.
0bd4127 [Reynold Xin] Fixed Python UDFs.
f9a0378 [Reynold Xin] Disable one more test.
5609494 [Reynold Xin] Disable some failing tests.
4efea20 [Reynold Xin] Don't check children resolved for UDF resolution.
2ebe549 [Reynold Xin] Removed more hardcoded functions.
aadce78 [Reynold Xin] [SPARK-7886] Use FunctionRegistry for built-in expressions in HiveContext.
Just replaced mutable.HashMap to ConcurrentHashMap
Author: navis.ryu <navis@apache.org>
Closes#6699 from navis/SPARK-7792 and squashes the following commits:
f03654a [navis.ryu] [SPARK-7792] [SQL] HiveContext registerTempTable not thread safe
This provides preliminary documentation pointing out how to use the
Hadoop free builds. I am hoping over time this list can grow to
include most of the popular Hadoop distributions.
Getting more people using these builds will help us long term reduce
the number of binaries we build.
Author: Patrick Wendell <patrick@databricks.com>
Closes#6729 from pwendell/hadoop-provided and squashes the following commits:
1113b76 [Patrick Wendell] [SPARK-6511] [Documentation] Explain how to use Hadoop provided builds
Just as a safeguard against DOM rewriting.
Author: Andrew Or <andrew@databricks.com>
Closes#6732 from andrewor14/dag-viz-trim and squashes the following commits:
7e9bacb [Andrew Or] [MINOR] [UI] DAG visualization: trim whitespace from input
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#6720 from MechCoder/empty_model_check and squashes the following commits:
3a07de5 [MechCoder] Remove construct to get weights in StreamingLinearAlgorithm
I noticed there is a duplicated description about WAL.
```
To ensure zero-data loss, you have to additionally enable Write Ahead Logs in Spark Streaming. To ensure zero data loss, enable the Write Ahead Logs (introduced in Spark 1.2).
```
Let's remove the duplication.
I don't file this issue in JIRA because it's minor.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#6719 from sarutak/remove-multiple-description and squashes the following commits:
cc9bb21 [Kousuke Saruta] Removed duplicated description about WAL
This patch switches to using FunctionRegistry for built-in expressions. It is based on #6463, but with some work to simplify it along with unit tests.
TODOs for future pull requests:
- Use static registration so we don't need to register all functions every time we start a new SQLContext
- Switch to using this in HiveContext
Author: Reynold Xin <rxin@databricks.com>
Author: Santiago M. Mola <santi@mola.io>
Closes#6710 from rxin/udf-registry and squashes the following commits:
6930822 [Reynold Xin] Fixed Python test.
b802c9a [Reynold Xin] Made UDF case insensitive.
e60d815 [Reynold Xin] Made UDF case insensitive.
852f9c0 [Reynold Xin] Fixed style violation.
e76a3c1 [Reynold Xin] Fixed parser.
52ddaba [Reynold Xin] Fixed compilation.
ee7854f [Reynold Xin] Improved error reporting.
ff906f2 [Reynold Xin] More robust constructor calling.
77b46f1 [Reynold Xin] Simplified the code.
2a2a149 [Reynold Xin] Merge pull request #6463 from smola/SPARK-7886
8616924 [Santiago M. Mola] [SPARK-7886] Add built-in expressions to FunctionRegistry.
Update to Netty 4.0.28-Final
Author: Sean Owen <sowen@cloudera.com>
Closes#6701 from srowen/SPARK-8101 and squashes the following commits:
f3b6369 [Sean Owen] Update to Netty 4.0.28-Final
