right() is documented on the wiki (
https://cwiki.apache.org/confluence/display/DRILL/SQL+Functions, last
edited 6 weeks ago), but doesn't seem to be a valid function:
use sys;
0: jdbc:drill:zk=local> select right("blahblah",2) from version;
Query failed: Query failed: Failure parsing SQL. Encount
Aditaya,
Thanks for working on this.
Here is drill bit log.
2015-02-13 14:28:51,498 [2b218572-dd78-a538-e9bb-547410c18cea:frag:1:0] ERROR
o.a.d.e.w.f.AbstractStatusReporter - Error
69c63002-9e29-471a-aacb-a073a421d37f: Failure while running fragment.
org.joda.time.IllegalFieldValueException:
Almost all of the heavy lifting has been done for us by calcite. See the
discussion here for a little bit of background and the parts we need to
still implement.
http://mail-archives.apache.org/mod_mbox/drill-dev/201501.mbox/%3CCAMpYv7APxne4JzM_wBrAtBd5Emkogj1jpnPeQQ3bA1E-7RKf=w...@mail.gmail.com%
I completely agree with that sentiment.
Given the Mongo and Cassandra plugin work that is being done, adding a JDBC
data source seems like it might be about the next most important to the
community as a whole.
On Fri, Feb 13, 2015 at 3:23 PM, Christopher Matta wrote:
> The potential for a JDBC
Andries,
Good thinking.
It works on csv file but not with MapR-DB table.
Here is the file showing that.
Thanks
Sudhakar Thota
On Feb 13, 2015, at 8:14 AM, Andries Engelbrecht
wrote:
> Does the CSV file work?
> Just not when in MaprDB?
> If so try varchar before to date.
>
> --Andries
The potential for a JDBC storage plugin has come up in discussions a lot
lately and would be a very positive addition to the project. I would love
to know if there's been any work on this, or if not how something like this
could get bootstrapped.
Chris Matta
cma...@mapr.com
215-701-3146
On Fri, F
I’m attempting to see if increased available memory to Drill has a positive
effect on certain queries, but I’m having trouble determining if changed
memory settings are being respected.
After setting DRILL_MAX_DIRECT_MEMORY="8G" and DRILL_MAX_HEAP="4G" I
restarted drill. Checking the *metrics* pag
I recall reading about development work on a JDBC storage plugin. Is this this
still being worked on? and if so, how can we get current status and/or
contribute?
thanks
February 13 2015 7:31 AM, "Uli Bethke" wrote:
> The use case of the adjunct data warehouse requires a data federation
> la
Drill definitely can serve as a database virtualization layer. Calcite was
used this way when it was just Optiq and Drill provides interesting
additional capabilities.
The emerging view of user needs seems to be tilting more towards the
semi-structured data capabilities of Drill rather than the v
You've hit the nail on the head in terms of challenges. The HDFS interface
doesn't provide an ability to specifically request certain data placement
strategies for a file. While placing the workload on a particular node
will likely create the first replica of data on that node, the secondary
repl
Thanks Aman. This answers my question. I suppose as a workaround for the
time being I could denormalize the smaller of the large tables into the
bigger one.
I would also be interested in the opinions of the group on data
co-locality (as implemented by Teradata). This is not so much a Drill
qu
Drill joins (either hash join or merge join) currently generate 3 types of
plans: hash distribute both sides of the join, hash distribute left side
and broadcast right side, broadcast right side and don't distribute left
side. These are cost-based decisions based on cardinalities. However, the
Thanks Jason.
Just a bit more background on my question. Modern MPPs such as Teradata
allow for full data co-locality via hash distribution of keys. This
ensures that join data of two large tables will always end up on the
same node and data co-locality is always ensured (no network overhead),
I don't think this actually answers your question. You can limit your
filters by directory to avoid reads from the filesystem, and some of the
storage plugins like Hbase and Hive implement scan level pushdown, but I do
not know if this is sophisticated enough that a join would be aware of the
parti
Does the CSV file work?
Just not when in MaprDB?
If so try varchar before to date.
--Andries
> On Feb 13, 2015, at 8:06 AM, Sudhakar Thota h wrote:
>
> Andries,
>
> The order date looks good I think as per the format.
>
>> | 3421989| Clerk#00601 | O | 1996-01-10 |
>> | 34229
Andries,
The order date looks good I think as per the format.
> | 3421989| Clerk#00601 | O | 1996-01-10 |
> | 3422915| Clerk#00058 | O | 1996-01-11 |
> | 3423106| Clerk#00266 | O | 1996-01-11 |
If you look at the output, it pulls the records for
yes you can read about it here
https://cwiki.apache.org/confluence/display/DRILL/Partition+Pruning
On Fri, Feb 13, 2015 at 6:42 AM, Uli Bethke wrote:
> I have two large tables in Hive (both partitioned and bucketed). Using Map
> side joins I can take advantage of data locality for the hash join
The use case of the adjunct data warehouse requires a data federation
layer between production warehouse analytics on Hadoop and the rest of
the EDW on an RDBMS.
The incumbents (Teradata, Oracle, SAS etc.) have proprietary offerings
in this space. PrestoDB also allows for federation between Ha
I have two large tables in Hive (both partitioned and bucketed). Using
Map side joins I can take advantage of data locality for the hash join
table.
Using Drill does the optimizer take the partitioning and bucketing into
consideration?
thanks
uli
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