Still have problem using HiveContext from sbt. Here’s an example of
dependencies:
|val sparkVersion = "1.4.0-rc3" lazy val root = Project(id =
"spark-hive", base = file("."), settings = Project.defaultSettings ++
Seq( name := "spark-1.4-hive", scalaVersion := "2.10.5",
scalaBinaryVersion := "2.10", resolvers += "Spark RC" at
"https://repository.apache.org/content/repositories/orgapachespark-1110/";,
libraryDependencies ++= Seq( "org.apache.spark" %% "spark-core" %
sparkVersion, "org.apache.spark" %% "spark-mllib" % sparkVersion,
"org.apache.spark" %% "spark-hive" % sparkVersion, "org.apache.spark" %%
"spark-sql" % sparkVersion ) )) |
Launching sbt console with it and running:
|val conf = new SparkConf().setMaster("local[4]").setAppName("test") val
sc = new SparkContext(conf) val sqlContext = new
org.apache.spark.sql.hive.HiveContext(sc) val data = sc.parallelize(1 to
10000) import sqlContext.implicits._ scala> data.toDF
java.lang.IllegalArgumentException: Unable to locate hive jars to
connect to metastore using classloader
scala.tools.nsc.interpreter.IMain$TranslatingClassLoader. Please set
spark.sql.hive.metastore.jars at
org.apache.spark.sql.hive.HiveContext.metadataHive$lzycompute(HiveContext.scala:206)
at
org.apache.spark.sql.hive.HiveContext.metadataHive(HiveContext.scala:175) at
org.apache.spark.sql.hive.HiveContext$anon$2.<init>(HiveContext.scala:367)
at
org.apache.spark.sql.hive.HiveContext.catalog$lzycompute(HiveContext.scala:367)
at org.apache.spark.sql.hive.HiveContext.catalog(HiveContext.scala:366)
at
org.apache.spark.sql.hive.HiveContext$anon$1.<init>(HiveContext.scala:379)
at
org.apache.spark.sql.hive.HiveContext.analyzer$lzycompute(HiveContext.scala:379)
at org.apache.spark.sql.hive.HiveContext.analyzer(HiveContext.scala:378)
at
org.apache.spark.sql.SQLContext$QueryExecution.assertAnalyzed(SQLContext.scala:901)
at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:134) at
org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:51) at
org.apache.spark.sql.SQLContext.createDataFrame(SQLContext.scala:474) at
org.apache.spark.sql.SQLContext.createDataFrame(SQLContext.scala:456) at
org.apache.spark.sql.SQLContext$implicits$.intRddToDataFrameHolder(SQLContext.scala:345)
|
Thanks,
Peter Rudenko
On 2015-06-01 05:04, Guoqiang Li wrote:
+1 (non-binding)
------------------ Original ------------------
*From: * "Sandy Ryza";<sandy.r...@cloudera.com>;
*Date: * Mon, Jun 1, 2015 07:34 AM
*To: * "Krishna Sankar"<ksanka...@gmail.com>;
*Cc: * "Patrick Wendell"<pwend...@gmail.com>;
"dev@spark.apache.org"<dev@spark.apache.org>;
*Subject: * Re: [VOTE] Release Apache Spark 1.4.0 (RC3)
+1 (non-binding)
Launched against a pseudo-distributed YARN cluster running Hadoop
2.6.0 and ran some jobs.
-Sandy
On Sat, May 30, 2015 at 3:44 PM, Krishna Sankar <ksanka...@gmail.com
<mailto:ksanka...@gmail.com>> wrote:
+1 (non-binding, of course)
1. Compiled OSX 10.10 (Yosemite) OK Total time: 17:07 min
mvn clean package -Pyarn -Dyarn.version=2.6.0 -Phadoop-2.4
-Dhadoop.version=2.6.0 -DskipTests
2. Tested pyspark, mlib - running as well as compare results with
1.3.1
2.1. statistics (min,max,mean,Pearson,Spearman) OK
2.2. Linear/Ridge/Laso Regression OK
2.3. Decision Tree, Naive Bayes OK
2.4. KMeans OK
Center And Scale OK
2.5. RDD operations OK
State of the Union Texts - MapReduce, Filter,sortByKey (word
count)
2.6. Recommendation (Movielens medium dataset ~1 M ratings) OK
Model evaluation/optimization (rank, numIter, lambda) with
itertools OK
3. Scala - MLlib
3.1. statistics (min,max,mean,Pearson,Spearman) OK
3.2. LinearRegressionWithSGD OK
3.3. Decision Tree OK
3.4. KMeans OK
3.5. Recommendation (Movielens medium dataset ~1 M ratings) OK
3.6. saveAsParquetFile OK
3.7. Read and verify the 4.3 save(above) - sqlContext.parquetFile,
registerTempTable, sql OK
3.8. result = sqlContext.sql("SELECT
OrderDetails.OrderID,ShipCountry,UnitPrice,Qty,Discount FROM
Orders INNER JOIN OrderDetails ON Orders.OrderID =
OrderDetails.OrderID") OK
4.0. Spark SQL from Python OK
4.1. result = sqlContext.sql("SELECT * from people WHERE State =
'WA'") OK
Cheers
<k/>
On Fri, May 29, 2015 at 4:40 PM, Patrick Wendell
<pwend...@gmail.com <mailto:pwend...@gmail.com>> wrote:
Please vote on releasing the following candidate as Apache
Spark version 1.4.0!
The tag to be voted on is v1.4.0-rc3 (commit dd109a8):
https://git-wip-us.apache.org/repos/asf?p=spark.git;a=commit;h=dd109a8746ec07c7c83995890fc2c0cd7a693730
The release files, including signatures, digests, etc. can be
found at:
http://people.apache.org/~pwendell/spark-releases/spark-1.4.0-rc3-bin/
<http://people.apache.org/%7Epwendell/spark-releases/spark-1.4.0-rc3-bin/>
Release artifacts are signed with the following key:
https://people.apache.org/keys/committer/pwendell.asc
The staging repository for this release can be found at:
[published as version: 1.4.0]
https://repository.apache.org/content/repositories/orgapachespark-1109/
[published as version: 1.4.0-rc3]
https://repository.apache.org/content/repositories/orgapachespark-1110/
The documentation corresponding to this release can be found at:
http://people.apache.org/~pwendell/spark-releases/spark-1.4.0-rc3-docs/
<http://people.apache.org/%7Epwendell/spark-releases/spark-1.4.0-rc3-docs/>
Please vote on releasing this package as Apache Spark 1.4.0!
The vote is open until Tuesday, June 02, at 00:32 UTC and passes
if a majority of at least 3 +1 PMC votes are cast.
[ ] +1 Release this package as Apache Spark 1.4.0
[ ] -1 Do not release this package because ...
To learn more about Apache Spark, please see
http://spark.apache.org/
== What has changed since RC1 ==
Below is a list of bug fixes that went into this RC:
http://s.apache.org/vN
== How can I help test this release? ==
If you are a Spark user, you can help us test this release by
taking a Spark 1.3 workload and running on this release candidate,
then reporting any regressions.
== What justifies a -1 vote for this release? ==
This vote is happening towards the end of the 1.4 QA period,
so -1 votes should only occur for significant regressions from
1.3.1.
Bugs already present in 1.3.X, minor regressions, or bugs related
to new features will not block this release.
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