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From 1.1.1 documentation, it seems one can use HiveContext instead of
SQLContext without having a Hive installation. The benefit is richer SQL
dialect.
Is my understanding correct ?
Thanks
That is correct. It the hive context will create an embedded metastore in
the current directory if you have not configured hive.
On Tue, Dec 9, 2014 at 5:51 PM, Manoj Samel manojsamelt...@gmail.com
wrote:
From 1.1.1 documentation, it seems one can use HiveContext instead of
SQLContext without
, Manoj Samel manojsamelt...@gmail.com
wrote:
From 1.1.1 documentation, it seems one can use HiveContext instead of
SQLContext without having a Hive installation. The benefit is richer SQL
dialect.
Is my understanding correct ?
Thanks
It works exactly like Create Table As Select (CTAS) in Hive.
Cheng Hao
From: Anas Mosaad [mailto:anas.mos...@incorta.com]
Sent: Wednesday, December 10, 2014 11:59 AM
To: Michael Armbrust
Cc: Manoj Samel; user@spark.apache.org
Subject: Re: Can HiveContext be used without using Hive
You can call .schema on SchemaRDDs. For example:
results.schema.fields.map(_.name)
On Sun, Dec 7, 2014 at 11:36 PM, abhishek reachabhishe...@gmail.com wrote:
Hi,
I have iplRDD which is a json, and I do below steps and query through
hivecontext. I get the results but without columns headers
Hi,
I have iplRDD which is a json, and I do below steps and query through
hivecontext. I get the results but without columns headers. Is there is a
way to get the columns names ?
val teamRDD = hiveContext.jsonRDD(iplRDD)
teamRDD.registerTempTable(teams)
hiveContext.cacheTable(teams)
val result
I'm getting this error when importing hive context
from pyspark.sql import HiveContext
Traceback (most recent call last):
File stdin, line 1, in module
File /path/spark-1.1.0/python/pyspark/__init__.py, line 63, in module
from pyspark.context import SparkContext
File /path/spark-1.1.0
pyspark.sql import HiveContext
Traceback (most recent call last):
File stdin, line 1, in module
File /path/spark-1.1.0/python/pyspark/__init__.py, line 63, in module
from pyspark.context import SparkContext
File /path/spark-1.1.0/python/pyspark/context.py, line 30, in module
Help please!
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.*
*E*: ji...@sellpoints.com
*M*: *510.303.7751*
On Thu, Nov 6, 2014 at 9:22 AM, tridib tridib.sama...@live.com wrote:
Help please!
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What version of Spark are you using? Did you compile your Spark version
and if so, what compile options did you use?
On 11/6/14, 9:22 AM, tridib tridib.sama...@live.com wrote:
Help please!
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sqlContext:
org.apache.spark.sql.hive.HiveContext
private local triedcooking
sqlContext
tpt // tree.tpe=org.apache.spark.sql.hive.HiveContext
Apply( // def init(sc: org.apache.spark.SparkContext):
org.apache.spark.sql.hive.HiveContext in class HiveContext,
tree.tpe
...@spark.incubator.apache.org
Subject: RE: Unable to use HiveContext in spark-shell
I am using spark 1.1.0.
I built it using:
./make-distribution.sh -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 -Phive
-DskipTests
My ultimate goal is to execute a query on parquet file with nested structure
and cast
Yes. I have org.apache.hadoop.hive package in spark assembly.
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I built spark-1.1.0 in a new fresh machine. This issue is gone! Thank you all
for your help.
Thanks Regards
Tridib
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I am connecting to a remote master using spark shell. Then I am getting
following error while trying to instantiate HiveContext.
scala val sqlContext = new org.apache.spark.sql.hive.HiveContext(sc)
error: bad symbolic reference. A signature in HiveContext.class refers to
term hive
in package
(spark.cassandra.connection.host,
127.0.0.1).set(spark.cleaner.ttl, 300)
val context = new SparkContext(conf)
val hiveContext = new HiveContext(context)
import com.dgm.Trail.hiveContext._
context textFile logs/log1.txt flatMap { data =
val Array(id, signals) = data split '|'
signals
There's an annoying small usability issue in HiveContext.
By default, it creates a local metastore which forbids other processes
using HiveContext to be launched from the same directory.
How can I make the metastore local to each HiveContext? Is there an
in-memory metastore configuration? /tmp
:
There's an annoying small usability issue in HiveContext.
By default, it creates a local metastore which forbids other processes
using HiveContext to be launched from the same directory.
How can I make the metastore local to each HiveContext? Is there an
in-memory metastore configuration
as metastore
https://db.apache.org/derby/docs/10.7/devguide/cdevdvlpinmemdb.html
I'll investigate this when free, guess we can use this for Spark SQL Hive
support testing.
On 10/27/14 4:38 PM, Jianshi Huang wrote:
There's an annoying small usability issue in HiveContext.
By default
Thanks Ted, this is exactly what Spark SQL LocalHiveContext does. To
make an embedded metastore local to a single HiveContext, we must
allocate different Derby database directories for each HiveContext, and
Jianshi is also trying to avoid that.
On 10/27/14 9:44 PM, Ted Yu wrote:
Please see
at 9:57 PM, Cheng Lian lian.cs@gmail.com wrote:
Thanks Ted, this is exactly what Spark SQL LocalHiveContext does. To make
an embedded metastore local to a single HiveContext, we must allocate
different Derby database directories for each HiveContext, and Jianshi is
also trying to avoid
HiveContext so that it can be
accessed from the JDBC Thrift Server.
I notice there are primarily only two methods available on the SchemaRDD
for data - saveAsTable and insertInto. One defines the schema while the
other can be used to insert in to the table, but there is no way to Alter
the table
:
Hi,
I have unstructured JSON as my input which may have extra columns row
to row. I want to store these json rows using HiveContext so that it
can be accessed from the JDBC Thrift Server.
I notice there are primarily only two methods available on the
SchemaRDD for data - saveAsTable
Is there any plan to support windowing queries? I know that Shark
supported it in its last release and expected it to be already included.
Someone from redhat is working on this. Unclear if it will make the 1.2
release.
| and |start-thriftserver.sh| under the same |$SPARK_HOME|
should work. Just verified this against Spark 1.1.
On 10/10/14 9:32 AM, Steve Arnold wrote:
I am writing a Spark job to persist data using HiveContext so that it
can be accessed via the JDBC Thrift server. Although my code doesn't
throw an error
I am writing a Spark job to persist data using HiveContext so that it can
be accessed via the JDBC Thrift server. Although my code doesn't throw an
error, I am unable to see my persisted data when I query from the Thrift
server.
I tried three different ways to get this to work:
1)
val
we have timestamp based duplicate removal which requires windowing
queries which are not working in SQLContext.sql parsing mode.
2. We then tried HiveQL using HiveContext by creating a Hive external table
backed by the same Parquet data. However, in this mode, projection pushdown
doesnt seem
We are working to improve the integration here, but I can recommend the
following when running spark 1.1: create an external table and
set spark.sql.hive.convertMetastoreParquet=true
Note that even with a HiveContext we don't support window functions yet.
On Wed, Oct 8, 2014 at 10:41 AM, Anand
...@spark.apache.org
Cc: user@spark.apache.orgmailto:user@spark.apache.org
user@spark.apache.orgmailto:user@spark.apache.org
Subject: Re: HiveContext: cache table not supported for partitioned table?
Cache table works with partitioned table.
I guess you’re experimenting with a default local metastore
Hi,
In Spark 1.1 HiveContext, I ran a create partitioned table command followed by
a cache table command and got a java.sql.SQLSyntaxErrorException: Table/View
'PARTITIONS' does not exist. But cache table worked fine if the table is not a
partitioned table.
Can anybody confirm that cache
Hi,
Would anybody know how to get the following information from HiveContext given
a Hive table name?
- partition key(s)
- table directory
- input/output format
I am new to Spark. And I have a couple tables created using Parquet data like:
CREATE EXTERNAL TABLE parquet_table (
COL1 string
We actually leave all the DDL commands up to hive, so there is no
programatic way to access the things you are looking for.
On Thu, Oct 2, 2014 at 5:17 PM, Banias calvi...@yahoo.com.invalid wrote:
Hi,
Would anybody know how to get the following information from HiveContext
given a Hive table
:39 AM, Du Li wrote:
Hi,
In Spark 1.1 HiveContext, I ran a create partitioned table command
followed by a cache table command and got
a java.sql.SQLSyntaxErrorException: Table/View 'PARTITIONS' does not
exist. But cache table worked fine if the table is not a partitioned
table.
Can anybody
...@yahoo.com.invalid wrote:
Hi,
Would anybody know how to get the following information from HiveContext given
a Hive table name?
- partition key(s)
- table directory
- input/output format
I am new to Spark. And I have a couple tables created using Parquet data like:
CREATE EXTERNAL TABLE parquet_table
NPE since the |Driver| is created in a
thread different from the one |HiveContext| (and the contained
|SessionState|) gets constructed.
On 9/19/14 3:31 AM, Du Li wrote:
I have figured it out.
As shown in the code below, if the HiveContext hc were created in the
actor object and used to create
causes NPE since the |Driver| is created in a
thread different from the one |HiveContext| (and the contained
|SessionState|) gets constructed.
On 9/19/14 3:31 AM, Du Li wrote:
I have figured it out.
As shown in the code below, if the HiveContext hc were created in the
actor object and used
I have figured it out.
As shown in the code below, if the HiveContext hc were created in the actor
object and used to create db in response to message, it would throw null
pointer exception. This is fixed by creating the HiveContext inside the MyActor
class instead. I also tested the code
Hi,
Wonder anybody had similar experience or any suggestion here.
I have an akka Actor that processes database requests in high-level messages.
Inside this Actor, it creates a HiveContext object that does the actual db
work. The main thread creates the needed SparkContext and passes
Hi, Du
I am not sure what you mean triggers the HiveContext to create a database, do
you create the sub class of HiveContext? Just be sure you call the
HiveContext.sessionState eagerly, since it will set the proper hiveconf
into the SessionState, otherwise the HiveDriver will always get
- dev
Is it possible that you are constructing more than one HiveContext in a
single JVM? Due to global state in Hive code this is not allowed.
Michael
On Wed, Sep 17, 2014 at 7:21 PM, Cheng, Hao hao.ch...@intel.com wrote:
Hi, Du
I am not sure what you mean “triggers the HiveContext
Hi there,
My product environment is AWS EMR with hadoop2.4.0 and spark1.0.2. I moved the
spark configuration in SPARK_CLASSPATH to spark-default.conf, then the
hiveContext went wrong.
I also found WARN info “WARN DataNucleus.General: Plugin (Bundle)
org.datanucleus.store.rdbms is already
Thanks for your reply.
Michael: No. I only create one HiveContext in the code.
Hao: Yes. I subclass HiveContext and defines own function to create database
and then subclass akka Actor to call that function in response to an abstract
message. By your suggestion, I called
println
Hi,
I have the following code snippet. It works fine on spark-shell but in a
standalone app it reports No TypeTag available for MySchema” at compile time
when calling hc.createScheamaRdd(rdd). Anybody knows what might be missing?
Thanks,
Du
--
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@spark.apache.orgmailto:user@spark.apache.org
user@spark.apache.orgmailto:user@spark.apache.org
Subject: SparkSQL HiveContext TypeTag compile error
Hi,
I have the following code snippet. It works fine on spark-shell but in a
standalone app it reports No TypeTag available for MySchema” at compile
, 2014 at 12:33 PM
To: user@spark.apache.orgmailto:user@spark.apache.org
user@spark.apache.orgmailto:user@spark.apache.org
Subject: Re: SparkSQL HiveContext TypeTag compile error
Solved it.
The problem occurred because the case class was defined within a test case in
FunSuite. Moving the case class
Hello Igor,
Although Decimal is supported, Hive 0.12 does not support user definable
precision and scale (it was introduced in Hive 0.13).
Thanks,
Yin
On Sat, Aug 30, 2014 at 1:50 AM, Zitser, Igor igor.zit...@citi.com wrote:
Hi All,
New to spark and using Spark 1.0.2 and hive 0.12.
If
/incubator-spark-user/201406.mbox/%3ccadoad2ks9_qgeign5-w7xogmrotrlbchvfukctgstj5qp9q...@mail.gmail.com%3E.
Currently using Spark-1.1 (grabbed from git two days ago) and using Hive 0.12
with my metastore in MySQL. If I run any HiveContext statements, it results in
cannot find the driver in CLASSPATH
Hi All,
New to spark and using Spark 1.0.2 and hive 0.12.
If hive table created as test_datatypes(testbigint bigint, ss bigint ) select
* from test_datatypes from spark works fine.
For create table test_datatypes(testbigint bigint, testdec decimal(5,2) )
scala val
Hi,
While using HiveContext.
If hive table created as test_datatypes(testbigint bigint, ss bigint ) select
below works fine.
For create table test_datatypes(testbigint bigint, testdec decimal(5,2) )
scala val dataTypes=hiveContext.hql(select * from test_datatypes)
14/08/28 21:18:44 INFO
-shell --master spark://S4:7077 --jars
/home/hduser/parquet-hive-bundle-1.5.0.jar
#import related hiveContext (successful)
...
# create parquet table:
hql(CREATE TABLE parquet_test (id int, str string, mp MAPSTRING,STRING,
lst ARRAYSTRING, strct STRUCTA:STRING,B:STRING) PARTITIONED BY (part
string) ROW
Thanks a lot. Finally, I can create parquet table using your command
-driver-class-path.
I am using hadoop 2.3. Now, I will try to load data into the tables.
Thanks,
lyc
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.
Thanks,
lyc
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/hduser/parquet-hive-bundle-1.5.0.jar
#import related hiveContext (successful)
...
# create parquet table:
hql(CREATE TABLE parquet_test (id int, str string, mp MAPSTRING,STRING,
lst ARRAYSTRING, strct STRUCTA:STRING,B:STRING) PARTITIONED BY (part
string) ROW FORMAT SERDE
...@yahoo.com.invalid wrote:
Hello All,
I have executed the following udf sql in my spark hivecontext,
hiveContext.hql(select count(t1.col1) from t1 join t2 where myUDF(t1.id ,
t2.id) = true)
Where do i find the count output?
Thanks and Regards,
Sankar S.
there is no collect_list in hive 0.12
try this after this ticket is done
https://issues.apache.org/jira/browse/SPARK-2706
i am also looking forward to this.
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I followed your instructions to try to load data as parquet format through
hiveContext but failed. Do you happen to know my uncorrectness in the
following steps?
The steps I am following is like:
1. download parquet-hive-bundle-1.5.0.jar
2. revise hive-site.xml including this:
property
on Hive 0.12.
That¹s what¹s worked for me.
Thanks,
Silvio
On 8/18/14, 3:14 PM, lyc yanchen@huawei.com wrote:
I followed your instructions to try to load data as parquet format through
hiveContext but failed. Do you happen to know my uncorrectness in the
following steps?
The steps I am
@huawei.com
Sent: 8/16/2014 12:56 AM
To: u...@spark.incubator.apache.orgmailto:u...@spark.incubator.apache.org
Subject: Re: Does HiveContext support Parquet?
Thank you for your reply.
Do you know where I can find some detailed information about how to use
Parquet in HiveContext?
Any information
Thanks for your help.
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from all
applications?
Best,
FP
On Aug 16, 2014 5:29 PM, lyc yanchen@huawei.com wrote:
Thanks for your help.
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If you're using HiveContext then all metadata is in the Hive metastore as
defined in hive-site.xml.
Concurrent writes should be fine as long as you're using a concurrent metastore
db.
From: Flavio Pompermaiermailto:pomperma...@okkam.it
Sent: 8/16/2014 1:26 PM
with the HiveContext. In 1.1 we have renamed this function to
registerTempTable to make this more clear.
2) If I have multiple hiveContexts (one per application) using the same
parquet table, is there any problem if inserting concurrently from all
applications?
This is not supported.
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Thank you for your reply.
Do you know where I can find some detailed information about how to use
Parquet in HiveContext?
Any information is appreciated.
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hive-thriftserver does not work with parquet tables in hive metastore also,
this PR will fix it too?
do not need to change any pom.xml ?
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I have a CDH5.0.3 cluster with Hive tables written in Parquet.
The tables have the DeprecatedParquetInputFormat on their metadata, and
when I try to select from one using Spark SQL, it blows up with a stack
trace like this:
java.lang.RuntimeException: java.lang.ClassNotFoundException:
As far as I can tell, the method was removed after 0.12.0 in the fix
for HIVE-5223
(https://github.com/apache/hive/commit/4059a32f34633dcef1550fdef07d9f9e044c722c#diff-948cc2a95809f584eb030e2b57be3993),
and that fix was back-ported in its entirety to 5.0.0+:
Hi Sean,
Thanks for the reply. I'm on CDH 5.0.3 and upgrading the whole cluster to
5.1.0 will eventually happen but not immediately.
I've tried running the CDH spark-1.0 release and also building it from
source. This, unfortunately goes into a whole other rathole of
dependencies. :-(
Eric
Hm, I was thinking that the issue is that Spark has to use a forked
hive-exec since hive-exec unfortunately includes a bunch of
dependencies it shouldn't. It forked Hive 0.12.0:
http://mvnrepository.com/artifact/org.spark-project.hive/hive-exec/0.12.0
... and then I was thinking maybe CDH wasn't
Yeah, that's what I feared. Unfortunately upgrades on very large production
clusters aren't a cheap way to find out what else is broken.
Perhaps I can create an RCFile table and sidestep parquet for now.
On Aug 10, 2014, at 1:45 PM, Sean Owen so...@cloudera.com wrote:
Hm, I was thinking
I imagine it's not the only instance of this kind of problem people
will ever encounter. Can you rebuild Spark with this particular
release of Hive?
Unfortunately the Hive APIs that we use change to much from release to
release to make this possible. There is a JIRA for compiling Spark SQL
Thanks Michael, I can try that too.
I know you guys aren't in sales/marketing (thank G-d), but given all the hoopla
about the CDH-DataBricks partnership, it'd be awesome if you guys were
somewhat more aligned, by which I mean that the DataBricks releases on Apache
that say for CDH5 would
If the link to PR/1819 is broken. Here is the one
https://github.com/apache/spark/pull/1819.
On Sun, Aug 10, 2014 at 5:56 PM, Eric Friedman eric.d.fried...@gmail.com
wrote:
Thanks Michael, I can try that too.
I know you guys aren't in sales/marketing (thank G-d), but given all the
hoopla
On Sun, Aug 10, 2014 at 2:43 PM, Michael Armbrust mich...@databricks.com
wrote:
if I try to add hive-exec-0.12.0-cdh5.0.3.jar to my SPARK_CLASSPATH, in
order to get DeprecatedParquetInputFormat, I find out that there is an
incompatibility in the SerDeUtils class. Spark's Hive snapshot
Hi,
When I try to use HiveContext in Spark shell on AWS, I got the error
java.lang.IllegalAccessError: tried to access method
com.google.common.collect.MapMaker.makeComputingMap(Lcom/google/common/base/Function;)Ljava/util/concurrent/ConcurrentMap.
I follow the steps below to compile and install
Hey Zhun,
Thanks for the detailed problem description. Please see my comments inlined
below.
On Thu, Aug 7, 2014 at 6:18 PM, Zhun Shen shenzhunal...@gmail.com wrote:
Caused by: java.lang.IllegalAccessError: tried to access method
Hi Cheng,
I replaced Guava 15.0 with Guava 14.0.1 in my spark classpath, the problem was
solved. So your method is correct. It proved that this issue was caused by AWS
EMR (ami-version 3.1.0) libs which include Guava 15.0.
Many thanks and see you in the first Spark User Beijing Meetup
the spark logs says? Enable debug mode to see what's
going on in spark-shell when it tries to interact and init HiveContext.
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Could you enable HistoryServer and provide the properties and CLASSPATH for the
spark-shell? And 'env' command to list your environment variables?
By the way, what does the spark logs says? Enable debug mode to see what's
going on in spark-shell when it tries to interact and init HiveContext
Thanks for the response... hive-site.xml is in the classpath so that doesn't
seem to be the issue.
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Hi,
Even though hive.metastore.warehouse.dir in hive-site.xml is set to the
default user/hive/warehouse and the permissions are correct in hdfs,
HiveContext seems to be creating metastore locally instead of hdfs. After
looking into the spark code, I found the following in HiveContext.scala
.applyOrElse(Analyzer.scala:113)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:165)
I
have read in the documentation that with HiveContext Spark SQL supports
all the UDFs supported in Hive.
I want to know if there is anything
else I need to follow to use Percentile
I have a problem with add jar command
hql(add jar /.../xxx.jar)
Error:
Exception in thread main java.lang.AssertionError: assertion failed: No
plan for AddJar ...
How could I do this job with HiveContext, I can't find any api to do it.
Does SparkSQL with Hive support UDF/UDAF?
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in thread main java.lang.AssertionError: assertion failed: No
plan for AddJar ...
How could I do this job with HiveContext, I can't find any api to do it.
Does SparkSQL with Hive support UDF/UDAF?
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to run the optimizer generate physical plans that slows down
the query.
Thanks,
Zongheng
On Wed, Jun 4, 2014 at 2:16 PM, ssb61 santoshbalma...@gmail.com wrote:
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mapPartitions at Exchange.scala:44 - 13 s
Thanks,
Santosh
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