+1. Excited to see more stateful workloads with Structured Streaming!
Best,
Burak
On Wed, Jan 10, 2024 at 8:21 AM Praveen Gattu
wrote:
> +1. This brings Structured Streaming a good solution for customers wanting
> to build stateful stream processing applications.
>
> On Wed, Jan 10, 2024 at
I'm also a +1 on the newer APIs. We had a lot of learnings from using
flatMapGroupsWithState and I believe that we can make the APIs a lot easier
to use.
On Wed, Nov 29, 2023 at 6:43 PM Anish Shrigondekar
wrote:
> Hi dev,
>
> Addressed the comments that Jungtaek had on the doc. Bumping the
+1 on adding to Spark. Community involvement will make the XML reader
better.
Best,
Burak
On Wed, Jul 19, 2023 at 3:25 AM Martin Andersson
wrote:
> Alright, makes sense to add it then.
> --
> *From:* Hyukjin Kwon
> *Sent:* Wednesday, July 19, 2023 11:01
> *To:*
My high level comment here is that as a naive person, I would expect a View
to be a special form of Table that SupportsRead but doesn't SupportWrite.
loadTable in the TableCatalog API should load both tables and views. This
way you avoid multiple RPCs to a catalog or data source or metastore, and
+1
Best,
Burak
On Tue, Jun 9, 2020 at 1:48 PM Shixiong(Ryan) Zhu
wrote:
> +1 (binding)
>
> Best Regards,
> Ryan
>
>
> On Tue, Jun 9, 2020 at 4:24 AM Wenchen Fan wrote:
>
>> +1 (binding)
>>
>> On Tue, Jun 9, 2020 at 6:15 PM Dr. Kent Yao wrote:
>>
>>> +1 (non-binding)
>>>
>>>
>>>
>>> --
>>>
Oh wow. I never thought this would be up for debate. I use complete mode
VERY frequently for all my dashboarding use cases. Here are some of my
thoughts:
> 1. It destroys the purpose of watermark and forces Spark to maintain all
of state rows, growing incrementally. It only works when all keys
Hey Russell,
Great catch on the documentation. It seems out of date. I honestly am
against having different DataSources having different default SaveModes.
Users will have no clue if a DataSource implementation is V1 or V2. It
seems weird that the default value can change for something that I
+1
On Mon, Mar 9, 2020 at 4:55 PM Reynold Xin wrote:
> +1
>
>
>
> On Mon, Mar 09, 2020 at 3:53 PM, John Zhuge wrote:
>
>> +1 (non-binding)
>>
>> On Mon, Mar 9, 2020 at 1:32 PM Michael Heuer wrote:
>>
>>> +1 (non-binding)
>>>
>>> I am disappointed however that this only mentions API and not
I can't imagine any Spark data source using Spark internals compiled on
Spark 2.4 working on 3.0 out of the box. There are many braking changes.
I'll try to get a *dev* branch for 3.0 soon (mid Jan).
Best,
Burak
On Mon, Dec 30, 2019, 8:53 AM Jean-Georges Perrin wrote:
> Hi there,
>
> Trying to
It depends on the data source. Delta Lake (https://delta.io) allows you to
do it with the .option("replaceWhere", "c = c1"). With other file formats,
you can write directly into the partition directory (tablePath/c=c1), but
you lose atomicity.
On Tue, May 7, 2019, 6:36 AM Shubham Chaurasia
Congrats Jose!
On Tue, Jan 29, 2019 at 10:50 AM Xiao Li wrote:
> Congratulations!
>
> Xiao
>
> Shixiong Zhu 于2019年1月29日周二 上午10:48写道:
>
>> Hi all,
>>
>> The Apache Spark PMC recently added Jose Torres as a committer on the
>> project. Jose has been a major contributor to Structured Streaming.
Probably just oversight. Anyone is welcome to add it :)
On Sun, Nov 25, 2018 at 8:55 AM Jacek Laskowski wrote:
> Hi,
>
> Why is FlatMapGroupsWithStateExec not measuring the time taken on state
> commit [1](like StreamingDeduplicateExec [2] and StreamingGlobalLimitExec
> [3])? Is this on
Hi Sandeep,
Watermarks are used in aggregation queries to ensure correctness and clean
up state. They don't allow you to drop records in map-only scenarios, which
you have in your example. If you would do a test of `groupBy().count()`
then you will see that the count doesn't increase with the
Congrats all! Well deserved.
On Sat, Mar 3, 2018 at 4:10 AM, Marco Gaido wrote:
> Congratulations to you all!
>
> On 3 Mar 2018 8:30 a.m., "Liang-Chi Hsieh" wrote:
>
>>
>> Congrats to everyone!
>>
>>
>> Kazuaki Ishizaki wrote
>> > Congratulations to
Hi Stavros,
Queryable state is definitely on the roadmap! We will revamp the StateStore
API a bit, and a queryable StateStore is definitely one of the things we
are thinking about during that revamp.
Best,
Burak
On Dec 8, 2017 9:57 AM, "Stavros Kontopoulos"
wrote:
>
I think if you don't cache the jdbc table, then it should auto-refresh.
On Mon, Nov 13, 2017 at 1:21 PM, spark receiver
wrote:
> Hi
>
> I’m using struct streaming(spark 2.2) to receive Kafka msg ,it works
> great. The thing is I need to join the Kafka message with a
+1
On Fri, Nov 3, 2017 at 10:02 PM, vaquar khan wrote:
> +1
>
> On Fri, Nov 3, 2017 at 8:14 PM, Weichen Xu
> wrote:
>
>> +1.
>>
>> On Sat, Nov 4, 2017 at 8:04 AM, Matei Zaharia
>> wrote:
>>
>>> +1 from me too.
>>>
>>>
Congrats Takuya!
On Mon, Feb 13, 2017 at 2:17 PM, Dilip Biswal wrote:
> Congratulations, Takuya!
>
> Regards,
> Dilip Biswal
> Tel: 408-463-4980 <(408)%20463-4980>
> dbis...@us.ibm.com
>
>
>
> - Original message -
> From: Takeshi Yamamuro
>
Thank you very much everyone! Hoping to help out the community as much as I
can!
Best,
Burak
On Tue, Jan 24, 2017 at 2:29 PM, Jacek Laskowski wrote:
> Wow! At long last. Congrats Burak and Holden!
>
> p.s. I was a bit worried that the process of accepting new committers
> is
Hi Maciej,
I believe it would be useful to either fix the documentation or fix the
implementation. I'll leave it to the community to comment on. The code
right now disallows intervals provided in months and years, because they
are not a "consistently" fixed amount of time. A month can be 28, 29,
+1
On Sep 29, 2016 4:33 PM, "Kyle Kelley" wrote:
> +1
>
> On Thu, Sep 29, 2016 at 4:27 PM, Yin Huai wrote:
>
>> +1
>>
>> On Thu, Sep 29, 2016 at 4:07 PM, Luciano Resende
>> wrote:
>>
>>> +1 (non-binding)
>>>
>>> On Wed, Sep 28,
I would really love something like this! It would be great if it doesn't
throw away corrupt_records like the Data Source.
On Wed, Sep 28, 2016 at 11:02 AM, Nathan Lande
wrote:
> We are currently pulling out the JSON columns, passing them through
> read.json, and then
Hi,
It's bad practice to change jars for the same version and is prohibited in
Spark Packages. Please bump your version number and make a new release.
Best regards,
Burak
On Tue, Jul 26, 2016 at 3:51 AM, Julio Antonio Soto de Vicente <
ju...@esbet.es> wrote:
> Hi all,
>
> Maybe I am missing
Hi Ismael and Jacek,
If you use Maven for building your applications, you may use the
spark-package command line tool (
https://github.com/databricks/spark-package-cmd-tool) to perform packaging.
It requires you to build your jar using maven first, and then does all the
extra magic that Spark
+1
On Tue, Mar 8, 2016 at 10:59 AM, Andrew Or wrote:
> +1
>
> 2016-03-08 10:59 GMT-08:00 Yin Huai :
>
>> +1
>>
>> On Mon, Mar 7, 2016 at 12:39 PM, Reynold Xin wrote:
>>
>>> +1 (binding)
>>>
>>>
>>> On Sun, Mar 6, 2016 at 12:08
Hi Yash,
I've run into multiple problems due to version incompatibilities, either
due to protobuf or jackson. That may be your culprit. The problem is that
all failures by the Kinesis Client Lib is silent, therefore don't show up
on the logs. It's very hard to debug those buggers.
Best,
Burak
Or you could also use reflection like in this Spark Package:
https://github.com/brkyvz/lazy-linalg/blob/master/src/main/scala/com/brkyvz/spark/linalg/BLASUtils.scala
Best,
Burak
On Mon, Nov 30, 2015 at 12:48 PM, DB Tsai wrote:
> The workaround is have your code in the same
+1. Tested complex R package support (Scala + R code), BLAS and DataFrame
fixes good.
Burak
On Thu, Sep 3, 2015 at 8:56 AM, mkhaitman wrote:
> Built and tested on CentOS 7, Hadoop 2.7.1 (Built for 2.6 profile),
> Standalone without any problems. Re-tested dynamic
Hi Yucheng,
Thanks for pointing out the issue. You are correct, in the case that the
final map is completely empty after the merge, we do need to add the final
element to the map, with the correct count (decrement the count with the
max count that was already in the map). I'll submit a fix for
shuffling given the blocks co-location?
Best regards, Alexander
*From:* Burak Yavuz [mailto:brk...@gmail.com]
*Sent:* Wednesday, July 15, 2015 3:29 PM
*To:* Ulanov, Alexander
*Cc:* Rakesh Chalasani; dev@spark.apache.org
*Subject:* Re: BlockMatrix multiplication
Hi Alexander,
I just
() - t) / 1e9)
Best regards, Alexander
*From:* Ulanov, Alexander
*Sent:* Tuesday, July 14, 2015 6:24 PM
*To:* 'Burak Yavuz'
*Cc:* Rakesh Chalasani; dev@spark.apache.org
*Subject:* RE: BlockMatrix multiplication
Hi Burak,
Thank you for explanation! I will try to make a diagonal
Hi Alexander,
From your example code, using the GridPartitioner, you will have 1 column,
and 5 rows. When you perform an A^T^A multiplication, you will generate a
separate GridPartitioner with 5 columns and 5 rows. Therefore you are
observing a huge shuffle. If you would generate a diagonal-block
+1 nonbinding.
On Thu, Jul 9, 2015 at 7:38 AM, Sean Owen so...@cloudera.com wrote:
+1 nonbinding. All previous RC issues appear resolved. All tests pass
with the -Pyarn -Phadoop-2.6 -Phive -Phive-thriftserver invocation.
Signatures et al are OK.
On Thu, Jul 9, 2015 at 6:55 AM, Patrick
Hi Ryan,
If you can get past the paperwork, I'm sure this can make a great Spark
Package (http://spark-packages.org). People then can use it for
benchmarking purposes, and I'm sure people will be looking for graph
generators!
Best,
Burak
On Wed, Jun 24, 2015 at 7:55 AM, Carr, J. Ryan
In addition, if you want to run a single suite, you may use:
mllib/testOnly $SUITE_NAME
with sbt.
On Jun 21, 2015 10:32 AM, Burak Yavuz brk...@gmail.com wrote:
You need to build an assembly jar for the cluster tests to pass. You may
use 'sbt assembly/assembly'.
Best,
Burak
On Jun 21, 2015 3
You need to build an assembly jar for the cluster tests to pass. You may
use 'sbt assembly/assembly'.
Best,
Burak
On Jun 21, 2015 3:43 AM, acidghost andreajemm...@gmail.com wrote:
After an sbt update the tests run. But all the cluster ones fail on task
size should be small in both training and
+1
Tested on Mac OS X
Burak
On Thu, Jun 4, 2015 at 6:35 PM, Calvin Jia jia.cal...@gmail.com wrote:
+1
Tested with input from Tachyon and persist off heap.
On Thu, Jun 4, 2015 at 6:26 PM, Timothy Chen tnac...@gmail.com wrote:
+1
Been testing cluster mode and client mode with mesos with
Hi Marcelo,
This is interesting. Can you please send me links to any failing builds if
you see that problem please. For now you can set a conf: `spark.jars.ivy`
to use a path except `~/.ivy2` for Spark.
Thanks,
Burak
On Thu, Jun 4, 2015 at 4:29 AM, Sean Owen so...@cloudera.com wrote:
I've
This is awesome! I can write the apps for it, to make the Web UI more
functional!
On Wed, Apr 1, 2015 at 12:37 AM, Tathagata Das tathagata.das1...@gmail.com
wrote:
This is a significant effort that Reynold has undertaken, and I am super
glad to see that it's finally taking a concrete form.
Hi,
We plan to add a more comprehensive local linear algebra package for MLlib
1.4. This local linear algebra package can then easily be extended to
BlockMatrix to support the same operations in a distributed fashion.
You may find the JIRA to track this here: SPARK-6442
Hi Kyle,
I'm actively working on it now. It's pretty close to completion, I'm just
trying to figure out bottlenecks and optimize as much as possible.
As Phase 1, I implemented multi model training on Gradient Descent. Instead of
performing Vector-Vector operations on rows (examples) and
+1. Tested MLlib algorithms on Amazon EC2, algorithms show speed-ups between
1.5-5x compared to the 1.0.2 release.
- Original Message -
From: Patrick Wendell pwend...@gmail.com
To: dev@spark.apache.org
Sent: Thursday, August 28, 2014 8:32:11 PM
Subject: Re: [VOTE] Release Apache Spark
Hi Guru,
Take a look at:
https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark
It has all the information you need on how to contribute to Spark. Also take a
look at:
https://issues.apache.org/jira/browse/SPARK/?selectedTab=com.atlassian.jira.jira-projects-plugin:summary-panel
Hi,
The roadmap for the 1.1 release and MLLib includes algorithms such as:
Non-negative matrix factorization, Sparse SVD, Multiclass
decision tree, Random Forests (?)
and optimizers such as:
ADMM, Accelerated gradient methods
also a statistical toolbox that includes:
descriptive statistics,
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