Hello everyone,
i am a member of nested group which has select priviledges.
Still not able to access Hive StoreOps Database,
Please suggest on this.
Thank you.
On Thu, May 21, 2015 at 9:30 AM, Anupam sinha wrote:
> I have upgrade of Hadoop cluster from 5.1.2 to 5.2.1.
> Now i am una
I have upgrade of Hadoop cluster from 5.1.2 to 5.2.1.
Now i am unable to read the hive tables,
before the upgrade i am able to access the Hive StoreOps Database.
Please suggest any changes i need to do
Here is the output i receive,
java.io.IOException: org.apache.hadoop.security.AccessControlEx
Hi ,
I'm trying to create a subset table from a master table which is stored in
ORC format. The query I'm using is :
CREATE TABLE tab_20150510 STORED AS ORC AS SELECT * FROM master_tab WHERE
col_id_60 <> '2015-05-20';
The master table is a table with 60 columns with all string data type but 1
c
Hi,
We are trying to create a Hive ORC Table with Tez. DDL command for the
same is
create table orc_table ROW FORMAT DELIMITED FIELDS TERMINATED BY '|' LINES
TERMINATED BY '\n'
STORED AS ORC AS select * from select_table;
However, it fails with the following error message:
M
Thank you Xuefu!
Excellent explanation and comparison!
We should put it to Hive on Spark wiki.
https://cwiki.apache.org/confluence/display/Hive/Hive+on+Spark
On Wed, May 20, 2015 at 10:45 AM, Xuefu Zhang wrote:
> I have been working on HIve on Spark, and knows a little about SparkSQL.
> Here a
I have been working on HIve on Spark, and knows a little about SparkSQL.
Here are a few factors to be considered:
1. SparkSQL is similar to Shark (discontinued) in that it clones Hive's
front end (parser and semantic analyzer) and metastore, and inject in
between a laryer where Hive's operator tre
What about outer lateral view?
On Wed, May 20, 2015 at 11:28 AM, matshyeq wrote:
> From my experience SparkSQL is still way faster than tez.
> Also, SparkSQL (even 1.2.1 which I'm on) supports *lateral view*
>
> On Wed, May 20, 2015 at 3:41 PM, Edward Capriolo
> wrote:
>
>> Beyond window querie
>From my experience SparkSQL is still way faster than tez.
Also, SparkSQL (even 1.2.1 which I'm on) supports *lateral view*
On Wed, May 20, 2015 at 3:41 PM, Edward Capriolo
wrote:
> Beyond window queries, hive still has concepts like cube or lateral view
> that many "better than hive" systems do
Beyond window queries, hive still has concepts like cube or lateral view
that many "better than hive" systems don't have.
Also now many people went around broadcasting SparkSQL/SparkSQL was/is
better/faster than hive but now that tez has "whooped" them in a benchmark
they are very quite.
http://w
While I've not experimented with the most recent versions of SparkSQL, earlier
releases could not cope with intermediate result sets that exceeded the
available memory; Hive handles this sort of situation much more gracefully. If
you have a smallish cluster and large data, this could pose a pro
Interesting question and one that I have asked myself. If you are
already heavily invested in the Hive ecosystem in terms of code and
skills I would look at Hive on Spark as my engine. In theory swapping
out engines (MR, TEZ, Spark) should be easy. Even though the devil is in
the detail.
SparkS
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