Dear friend,
thanks a ton was looking for linting for SQL for a long time, looks like
https://sqlfluff.com/ is something that can be used :)
Thank you so much, and wish you all a wonderful new year.
Regards,
Gourav
On Tue, Dec 26, 2023 at 4:42 AM Bjørn Jørgensen
wrote:
> You can try sqlfluff
Hi,
Holden Karau has some fantastic videos in her channel which will be quite
helpful.
Thanks
Gourav
On Sun, 16 Jul 2023, 19:15 Brian Huynh, wrote:
> Good morning Dipayan,
>
> Happy to see another contributor!
>
> Please go through this document for contributors. Please note the
>
Hi Khalid,
just out of curiosity, does the API help us in setting JOB ID's or just job
Descriptions?
Regards,
Gourav Sengupta
On Wed, Dec 28, 2022 at 10:58 AM Khalid Mammadov
wrote:
> There is a feature in SparkContext to set localProperties
> (setLocalProperty) where you can set your R
makes sense :)
Regards,
Gourav Sengupta
On Wed, Dec 28, 2022 at 4:13 AM Sean Owen wrote:
> I think this is kind of mixed up. Data warehouses are simple SQL
> creatures; Spark is (also) a distributed compute framework. Kind of like
> comparing maybe a web server to Java.
> Are you think
ong, SPARK used to be great in 2016-2017, but there are
superb alternatives now and the industry, in this recession, should focus
on getting more value for every single dollar they spend.
Best of luck.
Regards,
Gourav Sengupta
On Tue, Dec 27, 2022 at 7:30 PM Mich Talebzadeh
wrote:
> W
andalone deployment (even
> when ran on same k8s cluster)
>
> Sincerely,
>
> Leszek Reimus
>
>
>
>
> On Thu, Sep 29, 2022 at 7:06 PM Gourav Sengupta
> wrote:
>
>> Hi,
>>
>> dont containers finally run on systems, and the only advantage of
>> contain
on containers as well, and in EMR
running on EC2 nodes you can put all your binaries in containers and use
those for running your jobs.
Regards,
Gourav Sengupta
On Thu, Sep 29, 2022 at 7:46 PM Vladimir Prus
wrote:
> Igor,
>
> what exact instance types do you use? Unless you use local instance
Hi,
why not use EMR or data proc, kubernetes does not provide any benefit at
all for such scale of work. It is a classical case of over engineering and
over complication just for the heck of it.
Also I think that in case you are in AWS, Redshift Spectrum or Athena for
90% of use cases are way
Okay, so for the problem to the solution that is powerful
On Thu, 15 Sept 2022, 14:48 Mayur Benodekar, wrote:
> Hi Gourav,
>
> It’s the way the framework is
>
>
> Sent from my iPhone
>
> On Sep 15, 2022, at 02:02, Gourav Sengupta
> wrote:
>
>
> Hi,
>
Hi,
Why spark and why scala?
Regards,
Gourav
On Wed, 7 Sept 2022, 21:42 Mayur Benodekar, wrote:
> am new to scala and spark both .
>
> I have a code in scala which executes quieres in while loop one after the
> other.
>
> What we need to do is if a particular query takes more than a certain
Hi,
for some tasks as repartitionbyrange, it is indeed quite annoying sometimes
to wait for the maps to complete before reduce starts.
@Sean Owen do you have any comments?
Regards,
Gourav Sengupta
On Thu, Sep 8, 2022 at 12:10 AM Russell Jurney
wrote:
> I could be wrong , but… just st
if people using PySpark and Python
> UDFs find this proposed improvement useful.
>
> I see the proposed additional instrumentation as complementary to the
> Python/Pandas UDF Profiler introduced in Spark 3.3.
>
>
>
> Best,
>
> Luca
>
>
>
> *From:* Abdeali Kothari
Hi,
May be I am jumping to conclusions and making stupid guesses, but have you
tried koalas now that it is natively integrated with pyspark??
Regards
Gourav
On Thu, 25 Aug 2022, 11:07 Subash Prabanantham,
wrote:
> Hi All,
>
> I was wondering if we have any best practices on using pandas UDF ?
please be aware.
Are you in AWS? Please try DMS. If you are then that might be the best
solution depending on what you are looking for ofcourse.
If you are not in AWS, please let me know your environment, and I can help
you out.
Regards,
Gourav Sengupta
On Fri, Aug 19, 2022 at 1:13 PM sandra
, or redshift, or snowflake, they get a
lot more done with less overheads and heart aches. I particularly like how
native integration between ML systems like sagemaker works via redshift
queries, and aurora postgres - that is true unified data analytics at work.
Regards,
Gourav Sengupta
Regards,
Gourav
hi,
I do it with simple bash scripts to transfer to s3. Takes less than 1
minute to write it, and another 1 min to include it bootstrap scripts.
Never saw the need for so much hype for such simple tasks.
Regards,
Gourav Sengupta
On Tue, Aug 2, 2022 at 2:16 PM ayan guha wrote:
> ELK or Spl
defends the lack of support, and direction in this matter largely,
which is a joke.
Thanks and Regards,
Gourav Sengupta
On Mon, Aug 1, 2022 at 4:54 AM pengyh wrote:
>
> I don't think so. we were using spark integarted with Kafka for
> streaming computing and realtime reports. that j
on.
Thanks and Regards,
Gourav Sengupta
On Mon, Aug 1, 2022 at 1:58 AM pengyh wrote:
>
> I am afraid the most sql functions spark has the other BI tools also have.
>
> spark is used for high performance computing, not for SQL function
> comparisoin.
>
> Thanks.
>
Hi,
Agree with above response, but in case you are using arrow and transferring
data from JVM to python and back, then please try to check how are
things getting executed in python.
Please let me know what is the processing you are trying to do while using
arrow.
Regards,
Gourav Sengupta
Hi,
please try to query the table directly by loading the hive metastore (we
can do that quite easily in AWS EMR, but we can do things quite easily with
everything in AWS), rather than querying the s3 location directly.
Regards,
Gourav
On Wed, Jul 20, 2022 at 9:51 PM Joris Billen
wrote:
>
the SPARK system to read
it as a string first or use 100% scanning of the files to have a full
schema.
Regards,
Gourav Sengupta
On Wed, Jul 13, 2022 at 12:41 AM Muthu Jayakumar wrote:
> Hello Ayan,
>
> Thank you for the suggestion. But, I would lose correlation of the JSON
> file wi
Hi,
please see Sean's answer and please read about parallelism in spark.
Regards,
Gourav Sengupta
On Mon, Jul 11, 2022 at 10:12 AM Tufan Rakshit wrote:
> so as an average every 4 core , you get back 3.6 core in Yarn , but you
> can use only 3 .
> in Kubernetes you get back 3.6 and als
Hi,
SPARK is just one of the technologies out there now, there are several
other technologies far outperforming SPARK or at least as good as SPARK.
Regards,
Gourav
On Sat, Jul 2, 2022 at 7:42 PM Sid wrote:
> So as per the discussion, shuffle stages output is also stored on disk and
> not in
Please use EMR, Glue is not made for heavy processing jobs.
On Thu, Jun 23, 2022 at 6:36 AM Sid wrote:
> Hi Team,
>
> Could anyone help me in the below problem:
>
>
> https://stackoverflow.com/questions/72724999/how-to-calculate-number-of-g-1-workers-in-aws-glue-for-processing-1tb-data
>
>
Hi,
Just so that we understand the intention why do you need to know the
file size? Are you not using splittable file format?
If you use spark streaming to read the files, using just once, then you
will be able to get the metadata of the files I believe.
Regards,
Gourav Sengupta
On Sun, Jun
tch_count)
batch_id FROM
test).repartitionByRange("batch_id").createOrReplaceTempView("test_batch")
the above code should be able to then be run with a udf as long as we are
able to control the parallelism with the help of executor count and task
cpi configuration.
But once ag
a simple python program works quite well.
Regards,
Gourav
On Mon, Jun 13, 2022 at 9:28 AM Sid wrote:
> Hi Gourav,
>
> Do you have any examples or links, please? That would help me to
> understand.
>
> Thanks,
> Sid
>
> On Mon, Jun 13, 2022 at 1:42 PM Gourav Sengupta
&
Hi,
I think that serialising data using spark is an overkill, why not use
normal python.
Also have you tried repartition by range, that way you can use modulus
operator to batch things up?
Regards,
Gourav
On Mon, Jun 13, 2022 at 8:37 AM Sid wrote:
> Hi Team,
>
> I am trying to hit the POST
Hi,
just to elaborate what Ranadip has pointed out here correctly, gzip files
are read only by one executor, where as a bzip file can be read by multiple
executors therefore their reading speed will be parallelised and higher.
try to use bzip2 for kafka connect.
Regards,
Gourav Sengupta
On Mon
Hi,
can you please give us a simple map of what the input is and what the
output should be like? From your description it looks a bit difficult to
figure out what exactly or how exactly you want the records actually parsed.
Regards,
Gourav Sengupta
On Wed, May 25, 2022 at 9:08 PM Sid wrote
Hi,
in the spirit of not fitting the solution to the problem, would it not be
better to first create a producer for your job and use a broker like Kafka
or Kinesis or Pulsar?
Regards,
Gourav Sengupta
On Sat, May 21, 2022 at 3:46 PM Rohit Pant wrote:
> Hi all,
>
> I am trying to
Hi,
looks like spark listener is not working? Is your session still running?
Try to see the SPARK UI to find out whether the session is still active or
not
Regards,
Gourav
On Tue, May 3, 2022 at 7:37 PM Bjørn Jørgensen
wrote:
> I use jupyterlab and spark and I have not seen this before.
>
>
Hi,
this may not solve the problem, but have you tried to stop the job
gracefully, and then restart without much delay by pointing to a new
checkpoint location? The approach will have certain uncertainties for
scenarios where the source system can loose data, or we do not expect
duplicates to be
Hi,
did that result in valid JSON in the output file?
Regards,
Gourav Sengupta
On Tue, Apr 26, 2022 at 8:18 PM Sid wrote:
> I have .txt files with JSON inside it. It is generated by some API calls
> by the Client.
>
> On Wed, Apr 27, 2022 at 12:39 AM Bjørn Jørgensen
> w
Hi,
what is the version of spark are you using? And where is the data stored.
I am not quite sure that just using a bash script will help because
concatenating all the files into a single file creates a valid JSON.
Regards,
Gourav
On Tue, Apr 26, 2022 at 3:44 PM Sid wrote:
> Hello,
>
> Can
to
the output location?
Thanks and Regards,
Gourav Sengupta
On Fri, Apr 22, 2022 at 3:57 PM hsy...@gmail.com wrote:
> Hello all,
>
> I’m just trying to build a pipeline reading data from a streaming source
> and write to orc file. But I don’t see any file that is written to the
&
Hi,
have you checked skew settings in SPARK 3.2?
I am also not quite sure why you need a custom partitioner? While RDD still
remains a valid option you must try to explore the recent ways of thinking
and framing better solutions using SPARK.
Regards,
Gourav Sengupta
On Mon, Apr 11, 2022 at 4:47
Hi,
absolutely agree with Sean, besides that please see the release notes as
well for SPARK versions, they do mention about any issues around
compatibility
Regards,
Gourav
On Thu, Apr 7, 2022 at 6:32 PM Sean Owen wrote:
> (Don't cross post please)
> Generally you definitely want to compile and
Hi,
super duper.
Please try to see if you can write out the data to S3, and then write a
load script to load that data from S3 to HBase.
Regards,
Gourav Sengupta
On Wed, Apr 6, 2022 at 4:39 PM Joris Billen
wrote:
> HI,
> thanks for your reply.
>
>
> I believe I have found the
+ 1
Thanks and Regards,
Gourav Sengupta
On Mon, Apr 4, 2022 at 10:51 AM Joris Billen
wrote:
> Clear-probably not a good idea.
>
> But a previous comment said “you are doing everything in the end in one
> go”.
> So this made me wonder: in case your only action is a write in the e
and run.
Regards,
Gourav Sengupta
On Fri, Mar 25, 2022 at 1:19 PM Alex Ott wrote:
> You don't need to use foreachBatch to write to Cassandra. You just need to
> use Spark Cassandra Connector version 2.5.0 or higher - it supports native
> writing of stream data into Cassandra.
that set
me into data science and its applications.
Thanks Sean! :)
Regards,
Gourav Sengupta
On Tue, Mar 15, 2022 at 9:39 PM Artemis User wrote:
> Thanks Sean! Well, it looks like we have to abandon our structured
> streaming model to use DStream for this, or do you see possibility
Hi Jayesh,
thanks found your email quite interesting :)
Regards,
Gourav
On Wed, Mar 16, 2022 at 8:02 AM Bitfox wrote:
> Thank you. that makes sense.
>
> On Wed, Mar 16, 2022 at 2:03 PM Lalwani, Jayesh
> wrote:
>
>> The toDF function in scala uses a bit of Scala magic that allows you to
>>
ere) == count(
> partition_column ), but this may not work for complex queries.
>
>
> Regards
> Saurabh
> --
> *From:* Gourav Sengupta
> *Sent:* 05 March 2022 11:06
> *To:* Saurabh Gulati
> *Cc:* Mich Talebzadeh ; Kidong Lee <
> mykid..
. And the number of
records per file configuration should be mentioned in the following link as
maxrecordsperfile or something like that :
https://spark.apache.org/docs/latest/configuration.html#runtime-sql-configuration
.
Regards,
Gourav Sengupta
On Sat, Mar 5, 2022 at 5:09 PM Anil Dasari wrote
into it and kindly let me know if there is something
blocking me? I will be sincerely obliged.
Regards,
Gourav Sengupta
On Tue, Feb 22, 2022 at 3:58 PM Saurabh Gulati
wrote:
> Hey Mich,
> We use spark 3.2 now. We are using BQ but migrating away because:
>
>- Its not reflective of
;
>
>
> Regards
>
>
>
> *From: *Gourav Sengupta
> *Date: *Thursday, March 3, 2022 at 2:24 AM
> *To: *Anil Dasari
> *Cc: *Yang,Jie(INF) , user@spark.apache.org <
> user@spark.apache.org>
> *Subject: *Re: {EXT} Re: Spark Parquet write OOM
>
> Hi,
>
suggested)
let me know how things are giong on your end
Regards,
Gourav Sengupta
On Thu, Mar 3, 2022 at 8:37 AM Anil Dasari wrote:
> Answers in the context. Thanks.
>
>
>
> *From: *Gourav Sengupta
> *Date: *Thursday, March 3, 2022 at 12:13 AM
> *To: *Anil Dasari
> *C
Sengupta
On Wed, Mar 2, 2022 at 11:25 PM Anil Dasari wrote:
> 2nd attempt..
>
>
>
> Any suggestions to troubleshoot and fix the problem ? thanks in advance.
>
>
>
> Regards,
>
> Anil
>
>
>
> *From: *Anil Dasari
> *Date: *Wednesday, March 2, 2022 a
. Is your pipeline going to change or evolve soon, or the data volumes
going to vary, or particularly increase, over time?
4. What is the memory that you are having in your executors, and drivers?
5. Can you show the list of transformations that you are running ?
Regards,
Gourav Sengupta
On Wed
Hi,
why would you want to do that?
Regards,
Gourav
On Sat, Feb 26, 2022 at 8:00 AM wrote:
> such as this table definition:
>
> > desc people;
> +---+---+--+
> | col_name | data_type | comment |
>
RocksDB, it was introduced by Tathagata Das a few
years ago in the Databricks version, and it has now been made available in
the open source version, it really works well.
Let me know how things go, and what was your final solution.
Regards,
Gourav Sengupta
On Mon, Feb 28, 2022 at 6:02 AM karan
Hi,
May be the purpose of the article is different, but:
instead of: sources (trail files) --> kafka --> flume --> write to cloud
storage -->> SSS
a much simpler solution is: sources (trail files) --> write to cloud
storage -->> SSS
Putting additional components and hops just does sound a bit
Hi,
Can you please let us know:
1. the SPARK version, and the kind of streaming query that you are running?
2. whether you are using at least once, utmost once, or only once concepts?
3. any additional details that you can provide, regarding the storage
duration in Kafka, etc?
4. are your running
Dear Mich,
a super duper note of thanks, I had to spend around two weeks to figure
this out :)
Regards,
Gourav Sengupta
On Sat, Feb 26, 2022 at 10:43 AM Mich Talebzadeh
wrote:
>
>
> On Mon, 26 Apr 2021 at 10:21, Mich Talebzadeh
> wrote:
>
>>
>> Spark Structured
Hi,
not quite sure here, but can you please share your code?
Regards,
Gourav Sengupta
On Thu, Feb 24, 2022 at 8:25 PM Artemis User wrote:
> We got a Spark program that iterates through a while loop on the same
> input DataFrame and produces different results per iteration. I see
>
Hi,
can you please let us know the following:
1. the spark version
2. a few samples of input data
3. a few samples of what is the expected output that you want
Regards,
Gourav Sengupta
On Wed, Feb 23, 2022 at 8:43 PM karan alang wrote:
> Hello All,
>
> I'm using StructuredStreamin
opinion should
be fine I think.
Just like inspite of having Pandas UDF we went for Koalas, similarly SPARK
native integrations which are light weight and easy to use and extend to
deep learning frameworks perhaps makes sense according to me.
Regards,
Gourav Sengupta
Regards,
Gourav Sengupta
On Thu
, then what do we do? Because creating
professional quality data loaders is a very big job, therefore, these
solutions try to occupy that space as an entry point.
Regards,
Gourav Sengupta
On Thu, Feb 24, 2022 at 1:21 PM Bitfox wrote:
> I have been using tensorflow for a long time, it's not h
.
Regards,
Gourav Sengupta
On Wed, Feb 23, 2022 at 4:42 PM Dennis Suhari
wrote:
> Currently we are trying AnalyticsZoo and Ray
>
>
> Von meinem iPhone gesendet
>
> Am 23.02.2022 um 04:53 schrieb Bitfox :
>
>
> tensorflow itself can implement the distributed computing via a
Hi,
this looks like a very specific and exact problem in its scope.
Do you think that you can load the data into panda dataframe and load it
back to SPARK using PANDAS UDF?
Koalas is now natively integrated with SPARK, try to see if you can use
those features.
Regards,
Gourav
On Wed, Feb 23,
between Ray and SPARK.
Regards,
Gourav Sengupta
On Wed, Feb 23, 2022 at 12:35 PM Sean Owen wrote:
> Spark does do distributed ML, but not Tensorflow. Barrier execution mode
> is an element that things like Horovod uses. Not sure what you are getting
> at?
> Ray is not Spark.
> As I
so, and achieve that :)
I would sincerely request the open source SPARK community to prioritise
building the SPARK capabilities to scale ML applications.
Thanks and Regards,
Gourav Sengupta
On Wed, Feb 23, 2022 at 3:53 AM Bitfox wrote:
> tensorflow itself can implement the distribu
triggering the action of
query execution, and whether you are using SPARK Dataframes or SPARK SQL,
and the settings in SPARK (look at the settings for SPARK 3.x) and a few
other aspects you will see that the plan is quite cryptic and difficult to
read sometimes.
Regards,
Gourav Sengupta
On Sun, Feb 20
automate things.
Reading how to understand the plans may be good depending on what you are
trying to do.
Regards,
Gourav Sengupta
On Sat, Feb 19, 2022 at 10:00 AM Sid Kal wrote:
> I wrote a query like below and I am trying to understand its query
> execution plan.
>
> >>&
Hi Rico,
using SQL saves a lot of time, effort, and budget over the long term. But I
guess that there are certain joys in solving self induced complexities.
Thanks for sharing your findings.
Regards,
Gourav Sengupta
On Fri, Feb 18, 2022 at 7:26 AM Rico Bergmann wrote:
> I found the rea
.
Regards,
Gourav Sengupta
On Wed, Feb 9, 2022 at 8:51 PM karan alang wrote:
> Thanks, Mich .. will check it out
>
> regds,
> Karan Alang
>
> On Tue, Feb 8, 2022 at 3:06 PM Mich Talebzadeh
> wrote:
>
>> BTW you can check this Linkedin article of mine on Processing Cha
Hi,
can you please post a screen shot of the exact CAST statement that you are
using? Did you use the SQL method mentioned by me earlier?
Regards,
Gourav Sengupta
On Thu, Feb 17, 2022 at 12:17 PM Rico Bergmann wrote:
> hi!
>
> Casting another int column that is not a partition col
Hi,
This appears interesting, casting INT to STRING has never been an issue for
me.
Can you just help us with the output of : df.printSchema() ?
I prefer to use SQL, and the method I use for casting is: CAST(<> AS STRING) <>.
Regards,
Gourav
On Thu, Feb 17, 2022 at 6:02 AM Rico Bergmann
d them to run
economically, with security, costs and other implications for at least 3 to
4 years.
There is an old saying, do not fit the solution to the problem. May be I do
not understand the problem, and therefore saying all wrong things :)
Regards,
Gourav Sengupta
On Wed, Feb 16, 2022 at 3:31 P
the GPU's work fantastically well.
Regards,
Gourav Sengupta
On Wed, Feb 16, 2022 at 1:09 PM Sean Owen wrote:
> Spark itself does not use GPUs, and is agnostic to what GPUs exist on a
> cluster, scheduled by the resource manager, and used by an application.
> In practice, virtually all GP
Hi,
once again, just trying to understand the problem first.
Why are we using SPARK to place calls to micro services? There are several
reasons why this should never happen, including costs/ security/
scalability concerns, etc.
Is there a way that you can create a producer and put the data into
Hi,
sorry in case it appeared otherwise, Mich's takes are super interesting.
Just that while applying solutions on commercial undertakings things are
quite different from research/ development scenarios .
Regards,
Gourav Sengupta
On Mon, Feb 14, 2022 at 5:02 PM ashok34
Hi,
I would still not build any custom solution, and if in GCP use serverless
Dataproc. I think that it is always better to be hands on with AWS Glue
before commenting on it.
Regards,
Gourav Sengupta
On Mon, Feb 14, 2022 at 11:18 AM Mich Talebzadeh
wrote:
> Good question. However, we ou
use cloud - to reduce operational costs.
Sorry, just trying to understand what is the scope of this work.
Regards,
Gourav Sengupta
On Fri, Feb 11, 2022 at 8:35 PM Mich Talebzadeh
wrote:
> The equivalent of Google GKE autopilot
> <https://cloud.google.com/kubernetes-engine/docs/concepts/
Hi,
agree with Holden, have faced quite a few issues with FUSE.
Also trying to understand "spark-submit from local" . Are you submitting
your SPARK jobs from a local laptop or in local mode from a GCP dataproc /
system?
If you are submitting the job from your local laptop, there will be
hi,
Did you try to sorting while writing out the data? All of this engineering
may not be required in that case.
Regards,
Gourav Sengupta
On Sat, Feb 12, 2022 at 8:42 PM Chris Coutinho
wrote:
> Setting the option in the cluster configuration solved the issue, and now
> we'r
eading its settings.
Regards,
Gourav Sengupta
On Fri, Feb 11, 2022 at 6:00 PM Adam Binford wrote:
> Writing to Delta might not support the write.option method. We set
> spark.hadoop.parquet.block.size in our spark config for writing to Delta.
>
> Adam
>
> On Fri, Feb 11, 2022
Hi Anna,
Avro libraries should be inbuilt in SPARK in case I am not wrong. Any
particular reason why you are using a deprecated or soon to be deprecated
version of SPARK?
SPARK 3.2.1 is fantastic.
Please do let us know about your set up if possible.
Regards,
Gourav Sengupta
On Thu, Feb 10
, and there are different ways to manage that
depending on the SPARK version.
Thanks and Regards,
Gourav Sengupta
On Fri, Feb 11, 2022 at 11:09 AM frakass wrote:
> Hello list
>
> I have imported the data into spark and I found there is disk IO in
> every node. The memory didn't
Hi,
just so that we understand the problem first?
What is the source data (is it JSON, CSV, Parquet, etc)? Where are you
reading it from (JDBC, file, etc)? What is the compression format (GZ,
BZIP, etc)? What is the SPARK version that you are using?
Thanks and Regards,
Gourav Sengupta
On Fri
Hi,
so do you want to rank apple and tomato both as 2? Not quite clear on the
use case here though.
Regards,
Gourav Sengupta
On Tue, Feb 8, 2022 at 7:10 AM wrote:
>
> Hello Gourav
>
>
> As you see here orderBy has already give the solution for "equal
&
are trying to achieve by the rankings?
Regards,
Gourav Sengupta
On Tue, Feb 8, 2022 at 4:22 AM ayan guha wrote:
> For this req you can rank or dense rank.
>
> On Tue, 8 Feb 2022 at 1:12 pm, wrote:
>
>> Hello,
>>
>> For this query:
>>
>> >>&
records multiple times in a table, and still
have different values?
I think without knowing the requirements all the above responses, like
everything else where solutions are reached before understanding the
problem, has high chances of being wrong.
Regards,
Gourav Sengupta
On Mon, Feb 7, 2022
in the data of the filters first.
Regards,
Gourav Sengupta
On Mon, Jan 31, 2022 at 8:00 AM Benjamin Du wrote:
> I don't think coalesce (by repartitioning I assume you mean coalesce)
> itself and deserialising takes that much time. To add a little bit more
> context, the computation of the
are not actually solving the problem and just addressing the issue.
Regards,
Gourav Sengupta
On Wed, Jan 26, 2022 at 4:07 PM Sean Owen wrote:
> Really depends on what your UDF is doing. You could read 2GB of XML into
> much more than that as a DOM representation in memory.
> Remember 15GB of
to read the difference between repartition
and coalesce before making any kind of assumptions.
Regards,
Gourav Sengupta
On Sun, Jan 30, 2022 at 8:52 AM Sebastian Piu
wrote:
> It's probably the repartitioning and deserialising the df that you are
> seeing take time. Try doing this
>
?
There is a third option, which is akin to the second option that Mich was
mentioning, and that is basically a database transaction log, which gets
very large, very expensive to store and query over a period of time. Are
you creating a database transaction log?
Thanks and Regards,
Gourav Sengupta
On Thu, Jan 27
warnings in spark-shell using the
Logger.getLogger("akka").setLevel(Level.OFF) in case I have not completely
forgotten. Other details are mentioned here:
https://spark.apache.org/docs/latest/api/python/reference/api/pyspark.SparkContext.setLogLevel.html
Regards,
Gourav Sengupta
On Fri, Ja
Hi Amit,
before answering your question, I am just trying to understand it.
I am not exactly clear how do the Akka application, Kafka and SPARK
Streaming application sit together, and what are you exactly trying to
achieve?
Can you please elaborate?
Regards,
Gourav
On Fri, Jan 28, 2022 at
tasks to take care of
memory.
We do not have any other data regarding your clusters or environments
therefore it is difficult to imagine things and provide more information.
Regards,
Gourav Sengupta
On Thu, Jan 27, 2022 at 12:58 PM Aki Riisiö wrote:
> Ah, sorry for spamming, I found the ans
Hi,
may be I have less time, but can you please add some inline comments in
your code to explain what you are trying to do?
Regards,
Gourav Sengupta
On Tue, Jan 11, 2022 at 5:29 PM Alana Young wrote:
> I am experimenting with creating and persisting ML pipelines using custom
> transf
of the dataframe
in each iteration to understand the effect of your loops on the explain
plan - that should give some details.
Regards,
Gourav Sengupta
On Mon, Jan 10, 2022 at 10:49 PM Ramesh Natarajan
wrote:
> I want to compute cume_dist on a bunch of columns in a spark dataframe,
> but want to
art *=* i *** numRows
>
> end *=* start *+* numRows
>
> print("\ni:{} start:{} end:{}"*.*format(i, start,end))
>
> df *=* trainDF*.*iloc[ start:end ]
>
>
>
> There does not seem to be an easy way to do this.
>
>
> https://spark.apache.org/docs/lates
Hi,
I am a bit confused here, it is not entirely clear to me why are you
creating the row numbers, and how creating the row numbers helps you with
the joins?
Can you please explain with some sample data?
Regards,
Gourav
On Fri, Jan 7, 2022 at 1:14 AM Andrew Davidson
wrote:
> Hi
>
>
>
> I am
-ref-datatypes.html. Parquet is
definitely a columnar format, and if I am not entirely wrong, it definitely
supports columnar reading of data by default in SPARK.
Regards,
Gourav Sengupta
On Sun, Jan 9, 2022 at 2:34 PM weoccc wrote:
> Hi ,
>
> I want to store binary data (such as images)
Hi,
I am not sure at all that we need to use SQLContext and HiveContext
anymore.
Can you please check your JAVA_HOME, and SPARK_HOME? I use findspark
library to enable all environment variables for me regarding spark, or use
conda to install pyspark using conda-forge
Regards,
Gourav Sengupta
.rdd.getNumPartitions()
10
Please do refer to the following page for adaptive sql execution in SPARK
3, it will be of massive help particularly in case you are handling skewed
joins, https://spark.apache.org/docs/latest
Hi Andrew,
Any chance you might give Databricks a try in GCP?
The above transformations look complicated to me, why are you adding
dataframes to a list?
Regards,
Gourav Sengupta
On Sun, Dec 26, 2021 at 7:00 PM Andrew Davidson
wrote:
> Hi
>
>
>
> I am having trouble debu
> On Fri, Dec 24, 2021, 4:54 AM Gourav Sengupta
> wrote:
>
>> Hi,
>>
>> This question, once again like the last one, does not make much sense at
>> all. Where are you trying to store the data frame, and how?
>>
>> Are you just trying to write a blog, as
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