Re: Python for the kids and now PySpark

Mitch, you are right these days the attention span is getting shorter. Christian could work on a completely new thing for 3 hours and is proud to explain. It is amazing. Thanks for sharing. On Sat, Apr 27, 2024 at 9:40 PM Farshid Ashouri wrote: > Mich, this is absolutely amazing. > > Thanks

Re: Python for the kids and now PySpark

Mich, this is absolutely amazing. Thanks for sharing. On Sat, 27 Apr 2024, 22:26 Mich Talebzadeh, wrote: > Python for the kids. Slightly off-topic but worthwhile sharing. > > One of the things that may benefit kids is starting to learn something > new. Basically anything that can focus their

[Release Question]: Estimate on 3.5.2 release?

Hello, I'm curious if there is an estimate when 3.5.2 for Spark Core will be released. There are several bug and security vulnerability fixes in the dependencies we are excited to receive! If anyone has any insights, that would be greatly appreciated. Thanks! - ​Paul

[SparkListener] Accessing classes loaded via the '--packages' option

Hi folks, I'm contributing to the OpenLineage project, specifically the Apache Spark integration. My current focus is on extending the project to support data lineage extraction for Spark Streaming, beginning with Apache Kafka sources and sinks. I've encountered an obstacle when attempting to

unsubscribe

Re:RE: How to add MaxDOP option in spark mssql JDBC

Thank you. My main purpose is pass "MaxDop 1" to MSSQL to control the CPU usage. From the offical doc, I guess the problem of my codes is spark wrap the query to select * from (SELECT TOP 10 * FROM dbo.Demo with (nolock) WHERE Id = 1 option (maxdop 1)) spark_gen_alias Apparently, this

Re: [spark-graphframes]: Generating incorrect edges

Hi Mich, Thanks for your suggestions. 1) It currently runs on one server with plenty of resources assigned. But I will keep it in mind to replace monotonically_increasing_id() with uuid() once we scale up. 2) I have replaced the null values in origin with a string

DataFrameReader: timestampFormat default value

Is anyone familiar with [Datetime patterns]( https://spark.apache.org/docs/latest/sql-ref-datetime-pattern.html) and `TimestampType` parsing in PySpark? When reading CSV or JSON files, timestamp columns need to be parsed. via datasource property `timestampFormat`. [According to documentation](

Re: [spark-graphframes]: Generating incorrect edges

OK let us have a look at these 1) You are using monotonically_increasing_id(), which is not collision-resistant in distributed environments like Spark. Multiple hosts can generate the same ID. I suggest switching to UUIDs (e.g., uuid.uuid4()) for guaranteed uniqueness. 2) Missing values in

Re: [spark-graphframes]: Generating incorrect edges

Hi Mich, Thanks for your reply, 1) ID generation is done using monotonically_increasing_id() this is then prefixed with "p_", "m_", "o_" or "org_" depending on the

Re: [spark-graphframes]: Generating incorrect edges

OK few observations 1) ID Generation Method: How are you generating unique IDs (UUIDs, sequential numbers, etc.)? 2) Data Inconsistencies: Have you checked for missing values impacting ID generation? 3) Join Verification: If relevant, can you share the code for joining data points during ID

RE: How to add MaxDOP option in spark mssql JDBC

You might be able to leverage the prepareQuery option, that is at https://spark.apache.org/docs/3.5.1/sql-data-sources-jdbc.html#data-source-option ... this was introduced in Spark 3.4.0 to handle temp table query and CTE query against MSSQL server since what you send in is not actually what

[spark-graphframes]: Generating incorrect edges

tags: pyspark,spark-graphframes Hello, I am running pyspark in a podman container and I have issues with incorrect edges when I build my graph. I start with loading a source dataframe from a parquet directory on my server. The source dataframe has the following columns:

How to add MaxDOP option in spark mssql JDBC

[QUESTION] How to pass MAXDOP option · Issue #2395 · microsoft/mssql-jdbc (github.com) Hi team, I am suggested to require help form spark community. We suspect spark rewerite the query before pass to ms sql, and it lead to syntax error. Is there any work around to let make my codes work?

How to use Structured Streaming in Spark SQL

In Flink, you can create flow calculation tables using Flink SQL, and directly connect with SQL through CDC and Kafka. How to use SQL for flow calculation in Spark 308027...@qq.com

How to access the internal hidden columns of table by spark jdbc

I want to use spark jdbc to access alibaba cloud hologres (https://www.alibabacloud.com/product/hologres) internal hidden column `hg_binlog_timestamp_us ` but met the following error: Exception in thread "main" org.apache.spark.sql.AnalysisException: cannot resolve 'hg_binlog_timestamp_us'

Accounting the impact of failures in spark jobs

Hello, In my organization, we have an accounting system for spark jobs that uses the task execution time to determine how much time a spark job uses the executors for and we use it as a way to segregate cost. We sum all the task times per job and apply proportions. Our clusters follow a 1 task

StreamingQueryListener integration with Spark native metric sink (JmxSink)

Hi all, Is it possible to integrate StreamingQueryListener with Spark metrics so that metrics can be reported through Spark's internal metric system? Ideally, I would like to report some custom metrics through StreamingQueryListener and export them to Spark's JmxSink. Best, Mason

[ANNOUNCE] Apache Spark 3.4.3 released

We are happy to announce the availability of Apache Spark 3.4.3! Spark 3.4.3 is a maintenance release containing many fixes including security and correctness domains. This release is based on the branch-3.4 maintenance branch of Spark. We strongly recommend all 3.4 users to upgrade to this

[Spark SQL][How-To] Remove builtin function support from Spark

Hello, I'm very new to the Spark ecosystem, apologies if this question is a bit simple. I want to modify a custom fork of Spark to remove function support. For example, I want to remove the query runners ability to call reflect and java_method. I saw that there exists a data structure in

[Spark SQL][How-To] Remove builtin function support from Spark

Hello, I'm very new to the Spark ecosystem, apologies if this question is a bit simple. I want to modify a custom fork of Spark to remove function support. For example, I want to remove the query runners ability to call reflect and java_method. I saw that there exists a data structure in

should OutputCommitCoordinator fail stages for authorized committer failures when using s3a optimized committers?

In https://issues.apache.org/jira/browse/SPARK-39195, OutputCommitCoordinator was modified to fail a stage if an authorized committer task fails. We run our spark jobs on a k8s cluster managed by karpenter and mostly built from spot instances. As a result, our executors are frequently killed.

[Spark SQL] xxhash64 default seed of 42 confusion

Hi all, I've noticed that spark's xxhas64 output doesn't match other tool's due to using seed=42 as a default. I've looked at a few libraries and they use 0 as a default seed: - python https://github.com/ifduyue/python-xxhash - java https://github.com/OpenHFT/Zero-Allocation-Hashing/ - java

auto create event log directory if not exist

Spark history server is set to use s3a, like below spark.eventLog.enabled true spark.eventLog.dir s3a://bucket-test/test-directory-log any configuration option i can set on the Spark config such that if the directory 'test-directory-log' does not exist auto create it before start Spark history

Re: Spark streaming job for kafka transaction does not consume read_committed messages correctly.

Thanks, Mich for your reply. I agree, it is not so scalable and efficient. But it works correctly for kafka transaction, and there is no problem with committing offset to kafka async for now. I try to tell you some more details about my streaming job. CustomReceiver does not receive anything

Re: Spark streaming job for kafka transaction does not consume read_committed messages correctly.

Interesting My concern is infinite Loop in* foreachRDD*: The *while(true)* loop within foreachRDD creates an infinite loop within each Spark executor. This might not be the most efficient approach, especially since offsets are committed asynchronously.? HTH Mich Talebzadeh, Technologist |

Re: Spark streaming job for kafka transaction does not consume read_committed messages correctly.

Because spark streaming for kafk transaction does not work correctly to suit my need, I moved to another approach using raw kafka consumer which handles read_committed messages from kafka correctly. My codes look like the following. JavaDStream stream = ssc.receiverStream(new CustomReceiver());

Re: Spark streaming job for kafka transaction does not consume read_committed messages correctly.

Thank you Mich for your reply. Actually, I tried to do most of your advice. When spark.streaming.kafka.allowNonConsecutiveOffsets=false, I got the following error. Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 3)

Re: Spark streaming job for kafka transaction does not consume read_committed messages correctly.

Hi Kidong, There may be few potential reasons why the message counts from your Kafka producer and Spark Streaming consumer might not match, especially with transactional messages and read_committed isolation level. 1) Just ensure that both your Spark Streaming job and the Kafka consumer written

Spark streaming job for kafka transaction does not consume read_committed messages correctly.

Hi, I have a kafka producer which sends messages transactionally to kafka and spark streaming job which should consume read_committed messages from kafka. But there is a problem for spark streaming to consume read_committed messages. The count of messages sent by kafka producer transactionally is

Spark column headings, camelCase or snake case?

I know this is a bit of a silly question. But what is the norm for Sparkcolumn headings? Is it camelCase or snakec_ase. For example here " someone suggested and I quote SumTotalInMillionGBP" accurately conveys the meaning but is a bit long and uses camelCase, which is not the standard convention

Re: External Spark shuffle service for k8s

I think this answers your question about what to do if you need more space on nodes. https://spark.apache.org/docs/latest/running-on-kubernetes.html#local-storage Local Storage Spark supports using volumes to spill

Re: [Spark SQL]: Source code for PartitionedFile

Hi Mich, Thanks for the reply. I did come across that file but it didn't align with the appearance of `PartitionedFile`: https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/PartitionedFileUtil.scala In fact, the code snippet you shared also

Re: External Spark shuffle service for k8s

" In the end for my usecase I started using pvcs and pvc aware scheduling along with decommissioning. So far performance is good with this choice." How did you do this? tor. 11. apr. 2024 kl. 04:13 skrev Arun Ravi : > Hi Everyone, > > I had to explored IBM's and AWS's S3 shuffle plugins (some

Re: External Spark shuffle service for k8s

Hi Everyone, I had to explored IBM's and AWS's S3 shuffle plugins (some time back), I had also explored AWS FSX lustre in few of my production jobs which has ~20TB of shuffle operations with 200-300 executors. What I have observed is S3 and fax behaviour was fine during the write phase, however I

Re: Re: [Spark SQL] How can I use .sql() in conjunction with watermarks?

interesting. So below should be the corrected code with the suggestion in the [SPARK-47718] .sql() does not recognize watermark defined upstream - ASF JIRA (apache.org) # Define schema for parsing Kafka messages schema = StructType([

Re: Re: [Spark SQL] How can I use .sql() in conjunction with watermarks?

Sorry this is not a bug but essentially a user error. Spark throws a really confusing error and I'm also confused. Please see the reply in the ticket for how to make things correct. https://issues.apache.org/jira/browse/SPARK-47718 刘唯 于2024年4月6日周六 11:41写道： > This indeed looks like a bug. I will

Re: How to get db related metrics when use spark jdbc to read db table?

If you're using just Spark you could try turning on the history server and try to glean statistics from there. But there is no one location or log file which stores them all. Databricks, which is a managed Spark solution, provides such

Re: [Spark SQL]: Source code for PartitionedFile

Hi, I believe this is the package https://raw.githubusercontent.com/apache/spark/master/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FilePartition.scala And the code case class FilePartition(index: Int, files: Array[PartitionedFile]) extends Partition with

Re: How to get db related metrics when use spark jdbc to read db table?

Well you can do a fair bit with the available tools The Spark UI, particularly the Staging and Executors tabs, do provide some valuable insights related to database health metrics for applications using a JDBC source. Stage Overview: This section provides a summary of all the stages executed

[Spark SQL]: Source code for PartitionedFile

Hi All, I've been diving into the source code to get a better understanding of how file splitting works from a user perspective. I've hit a deadend at `PartitionedFile`, for which I cannot seem to find a definition? It appears though it should be found at

Re: External Spark shuffle service for k8s

Hi, First thanks everyone for their contributions I was going to reply to @Enrico Minack but noticed additional info. As I understand for example, Apache Uniffle is an incubating project aimed at providing a pluggable shuffle service for Spark. So basically, all these "external shuffle

Re: External Spark shuffle service for k8s

I see that both Uniffle and Celebron support S3/HDFS backends which is great. In the case someone is using S3/HDFS, I wonder what would be the advantages of using Celebron or Uniffle vs IBM shuffle service plugin or Cloud Shuffle Storage Plugin from AWS

How to get db related metrics when use spark jdbc to read db table?

Hello, I have a spark application with jdbc source and do some calculation. To monitor application healthy, I need db related metrics per database like number of connections, sql execution time and sql fired time distribution etc. Does anybody know how to get them? Thanks!

Re: External Spark shuffle service for k8s

Apache Uniffle (incubating) may be another solution. You can see https://github.com/apache/incubator-uniffle https://uniffle.apache.org/blog/2023/07/21/Uniffle%20-%20New%20chapter%20for%20the%20shuffle%20in%20the%20cloud%20native%20era Mich Talebzadeh 于2024年4月8日周一 07:15写道： > Splendid > > The

Re: External Spark shuffle service for k8s

There is Apache incubator project Uniffle: https://github.com/apache/incubator-uniffle It stores shuffle data on remote servers in memory, on local disk and HDFS. Cheers, Enrico Am 06.04.24 um 15:41 schrieb Mich Talebzadeh: I have seen some older references for shuffle service for k8s,

Spark UDAF in examples fail with not serializable error

The type-safe example given at https://spark.apache.org/docs/latest/sql-ref-functions-udf-aggregate.html fails with a not serializable exception Is this a known issue?

Re: Idiomatic way to rate-limit streaming sources to avoid OutOfMemoryError?

OK, This is a common issue in Spark Structured Streaming (SSS), where the source generates data faster than Spark can process it. SSS doesn't have a built-in mechanism for directly rate-limiting the incoming data stream itself. However, consider the following: - Limit the rate at which data

Re: External Spark shuffle service for k8s

Thanks Cheng for the heads up. I will have a look. Cheers Mich Talebzadeh, Technologist | Solutions Architect | Data Engineer | Generative AI London United Kingdom view my Linkedin profile

Re: External Spark shuffle service for k8s

There is an IBM shuffle service plugin that supports S3 https://github.com/IBM/spark-s3-shuffle Though I would think a feature like this could be a part of the main Spark repo. Trino already has out-of-box support for s3 exchange (shuffle) and it's very useful. Vakaris On Sun, Apr 7, 2024 at

Idiomatic way to rate-limit streaming sources to avoid OutOfMemoryError?

Hi Spark community, I have a Spark Structured Streaming application that reads data from a socket source (implemented very similarly to the TextSocketMicroBatchStream). The issue is that the source can generate data faster than Spark can process it, eventually leading to an OutOfMemoryError

Re: External Spark shuffle service for k8s

Instead of External Shuffle Shufle, Apache Celeborn might be a good option as a Remote Shuffle Service for Spark on K8s. There are some useful resources you might be interested in. [1] https://celeborn.apache.org/ [2] https://www.youtube.com/watch?v=s5xOtG6Venw [3]

Re: External Spark shuffle service for k8s

Splendid The configurations below can be used with k8s deployments of Spark. Spark applications running on k8s can utilize these configurations to seamlessly access data stored in Google Cloud Storage (GCS) and Amazon S3. For Google GCS we may have spark_config_gcs = {

Example UDAF fails with "not serializable" exception

https://spark.apache.org/docs/3.3.2/sql-ref-functions-udf-aggregate.html I'm trying to run this example on Databricks, and it fails with the stacktrace below. It's literally a copy-paste from the example, what am I missing? Job aborted due to stage failure: Task not serializable:

Re: External Spark shuffle service for k8s

Thanks for your suggestion that I take it as a workaround. Whilst this workaround can potentially address storage allocation issues, I was more interested in exploring solutions that offer a more seamless integration with large distributed file systems like HDFS, GCS, or S3. This would ensure

Re: External Spark shuffle service for k8s

You can make a PVC on K8S call it 300GB make a folder in yours dockerfile WORKDIR /opt/spark/work-dir RUN chmod g+w /opt/spark/work-dir start spark with adding this .config("spark.kubernetes.driver.volumes.persistentVolumeClaim.300gb.options.claimName", "300gb") \

Re: Re: [Spark SQL] How can I use .sql() in conjunction with watermarks?

This indeed looks like a bug. I will take some time to look into it. Mich Talebzadeh 于2024年4月3日周三 01:55写道： > > hm. you are getting below > > AnalysisException: Append output mode not supported when there are > streaming aggregations on streaming DataFrames/DataSets without watermark; > > The

Re: [External] Re: Issue of spark with antlr version

[[VOTE] Release Plan for Apache Spark 4.0.0 (June 2024)]( https://lists.apache.org/thread/r0zn6rd8y25yn2dg59ktw3ttrwxzqrfb) Apache Spark 4.0.0 Release Plan === 1. After creating `branch-3.5`, set "4.0.0-SNAPSHOT" in master branch. 2. Creating `branch-4.0` on April

Unsubscribe

Unsubscribe - To unsubscribe e-mail: user-unsubscr...@spark.apache.org

External Spark shuffle service for k8s

I have seen some older references for shuffle service for k8s, although it is not clear they are talking about a generic shuffle service for k8s. Anyhow with the advent of genai and the need to allow for a larger volume of data, I was wondering if there has been any more work on this matter.

Clarification on what "[id=#]" refers to in Physical Plan Exchange hashpartitioning

Hello, While looking through spark physical plans generated by the spark history server log to find any bottle necks in my code, I stumbled across an ID that shows up in a partitioning stage. My goal is to use the history server log to provide meaningful analysis on my spark system

Clarification on what "[id=#]" refers to in Physical Plan Exchange hashpartitioning

Hello, While looking through spark physical plans generated by the spark history server log to find any bottle necks in my code, I stumbled across an ID that shows up in a partitioning stage. My goal is to use the history server log to provide meaningful analysis on my spark system

Re: [EXTERNAL] Re: [Spark]: Spark / Iceberg / hadoop-aws compatibility matrix

I don't really understand how Iceberg and the hadoop libraries can coexist in a deployment. The latest spark (3.5.1) base image contains the hadoop-client*-3.3.4.jar. The AWS v2 SDK is only supported in hadoop*-3.4.0.jar and onward. Iceberg AWS integration states AWS v2 SDK is

Re: [EXTERNAL] Re: [Spark]: Spark / Iceberg / hadoop-aws compatibility matrix

Swapping out the iceberg-aws-bundle for the very latest aws provided sdk ('software.amazon.awssdk:bundle:2.25.23') produces an incompatibility from a slightly different code path: java.lang.NoSuchMethodError: 'void

Participate in the ASF 25th Anniversary Campaign

Hi everyone, As part of The ASF’s 25th anniversary campaign[1], we will be celebrating projects and communities in multiple ways. We invite all projects and contributors to participate in the following ways: * Individuals - submit your first contribution:

Re: [EXTERNAL] Re: [Spark]: Spark / Iceberg / hadoop-aws compatibility matrix

[sorry; replying all this time] With hadoop-*-3.3.6 in place of the 3.4.0 below I get java.lang.NoClassDefFoundError: com/amazonaws/AmazonClientException I think that the below iceberg-aws-bundle version supplies the v2 sdk. Dan From: Aaron Grubb Sent: 03

Re: [Spark]: Spark / Iceberg / hadoop-aws compatibility matrix

Downgrade to hadoop-*:3.3.x, Hadoop 3.4.x is based on the AWS SDK v2 and should probably be considered as breaking for tools that build on < 3.4.0 while using AWS. From: Oxlade, Dan Sent: Wednesday, April 3, 2024 2:41:11 PM To: user@spark.apache.org Subject:

[Spark]: Spark / Iceberg / hadoop-aws compatibility matrix

Hi all, I've struggled with this for quite some time. My requirement is to read a parquet file from s3 to a Dataframe then append to an existing iceberg table. In order to read the parquet I need the hadoop-aws dependency for s3a:// . In order to write to iceberg I need the iceberg dependency.

Re: Re: [Spark SQL] How can I use .sql() in conjunction with watermarks?

hm. you are getting below AnalysisException: Append output mode not supported when there are streaming aggregations on streaming DataFrames/DataSets without watermark; The problem seems to be that you are using the append output mode when writing the streaming query results to Kafka. This mode

RE: Re: [Spark SQL] How can I use .sql() in conjunction with watermarks?

Hi Mich, Thank you so much for your response. I really appreciate your help! You mentioned "defining the watermark using the withWatermark function on the streaming_df before creating the temporary view” - I believe this is what I’m doing and it’s not working for me. Here is the exact code

Re: [Spark SQL] How can I use .sql() in conjunction with watermarks?

ok let us take it for a test. The original code of mine def fetch_data(self): self.sc.setLogLevel("ERROR") schema = StructType() \ .add("rowkey", StringType()) \ .add("timestamp", TimestampType()) \ .add("temperature", IntegerType())

[Spark SQL] How can I use .sql() in conjunction with watermarks?

Hello! I am attempting to write a streaming pipeline that would consume data from a Kafka source, manipulate the data, and then write results to a downstream sink (Kafka, Redis, etc). I want to write fully formed SQL instead of using the function API that Spark offers. I read a few guides on

Re: [External] Re: Issue of spark with antlr version

Hi Team, Can you let us know the when this spark 4.x will be released to maven. regards, Parul Get Outlook for iOS From: Bjørn Jørgensen Sent: Wednesday, February 28, 2024 5:06:54 PM To: Chawla, Parul Cc: Sahni, Ashima ;

Apache Spark integration with Spring Boot 3.0.0+

Hello, Ive got a project which has to use newest versions of both Apache Spark and Spring Boot due to vulnerabilities issues. I build my project using Gradle. And when I try to run it i get : Unsatisfied dependecy exception about javax/servlet/Servlet. Ive tried to add jakarta servlet,

Community Over Code NA 2024 Travel Assistance Applications now open!

Hello to all users, contributors and Committers! [ You are receiving this email as a subscriber to one or more ASF project dev or user mailing lists and is not being sent to you directly. It is important that we reach all of our users and contributors/committers so that they may get a chance

Re: [DISCUSS] MySQL version support policy

Hi, Cheng. Thank you for the suggestion. Your suggestion seems to have at least two themes. A. Adding a new Apache Spark community policy (contract) to guarantee MySQL LTS Versions Support. B. Dropping the support of non-LTS version support (MySQL 8.3/8.2/8.1) And, it brings me three questions.

[DISCUSS] MySQL version support policy

Hi, Spark community, I noticed that the Spark JDBC connector MySQL dialect is testing against the 8.3.0[1] now, a non-LTS version. MySQL changed the version policy recently[2], which is now very similar to the Java version policy. In short, 5.5, 5.6, 5.7, 8.0 is the LTS version, 8.1, 8.2, 8.3

Is one Spark partition mapped to one and only Spark Task ?

I am trying to understand the Spark Architecture for my upcoming certification, however there seems to be conflicting information available. https://stackoverflow.com/questions/47782099/what-is-the-relationship-between-tasks-and-partitions Does Spark assign a Spark partition to only a single

Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

+1 -- Thank You & Best Regards Winston Lai From: Jay Han Date: Sunday, 24 March 2024 at 08:39 To: Kiran Kumar Dusi Cc: Farshid Ashouri , Matei Zaharia , Mich Talebzadeh , Spark dev list , user @spark Subject: Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

+1. It sounds awesome! Kiran Kumar Dusi 于2024年3月21日周四 14:16写道： > +1 > > On Thu, 21 Mar 2024 at 7:46 AM, Farshid Ashouri < > farsheed.asho...@gmail.com> wrote: > >> +1 >> >> On Mon, 18 Mar 2024, 11:00 Mich Talebzadeh, >> wrote: >> >>> Some of you may be aware that Databricks community Home |

Re: Feature article: Leveraging Generative AI with Apache Spark: Transforming Data Engineering

Sorry from this link Leveraging Generative AI with Apache Spark: Transforming Data Engineering | LinkedIn Mich Talebzadeh, Technologist | Data | Generative AI |

Feature article: Leveraging Generative AI with Apache Spark: Transforming Data Engineering

You may find this link of mine in Linkedin for the said article. We can use Linkedin for now. Leveraging Generative AI with Apache Spark: Transforming Data Engineering | LinkedIn Mich Talebzadeh, Technologist | Data | Generative AI | Financial Fraud London United Kingdom view my Linkedin

Re:

You can try this val kafkaReadStream = spark .readStream .format("kafka") .option("kafka.bootstrap.servers", broker) .option("subscribe", topicName) .option("startingOffsets", startingOffsetsMode) .option("maxOffsetsPerTrigger", maxOffsetsPerTrigger) .load() kafkaReadStream

Bug in org.apache.spark.util.sketch.BloomFilter

Hi All, I believe that there is a bug that affects the Spark BloomFilter implementation when creating a bloom filter with large n. Since this implementation uses integer hash functions, it doesn’t work properly when the number of bits exceeds MAX_INT. I asked a question about this on

[no subject]

Hi! I want to exucute code inside forEachBatch that will trigger regardless of whether there is data in the batch or not. val kafkaReadStream = spark .readStream .format("kafka") .option("kafka.bootstrap.servers", broker) .option("subscribe", topicName) .option("startingOffsets",

Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

+1 On Thu, 21 Mar 2024 at 7:46 AM, Farshid Ashouri wrote: > +1 > > On Mon, 18 Mar 2024, 11:00 Mich Talebzadeh, > wrote: > >> Some of you may be aware that Databricks community Home | Databricks >> have just launched a knowledge sharing hub. I thought it would be a >> good idea for the Apache

Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

+1 On Mon, 18 Mar 2024, 11:00 Mich Talebzadeh, wrote: > Some of you may be aware that Databricks community Home | Databricks > have just launched a knowledge sharing hub. I thought it would be a > good idea for the Apache Spark user group to have the same, especially > for repeat questions on

Announcing the Community Over Code 2024 Streaming Track

Hi all, Community Over Code , the ASF conference, will be held in Denver, Colorado, October 7-10, 2024. The call for presentations is open

Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

One option that comes to my mind, is that given the cyclic nature of these types of proposals in these two forums, we should be able to use Databricks's existing knowledge sharing hub Knowledge Sharing Hub - Databricks

Spark-UI stages and other tabs not accessible in standalone mode when reverse-proxy is enabled

Hi Team, We're encountering an issue with Spark UI. I've documented the details here: https://issues.apache.org/jira/browse/SPARK-47232 When enabled reverse proxy in master and worker configOptions. We're not able to access different tabs available in spark UI e.g.(stages, environment, storage

Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

+1 On 18 Mar 2024, at 21:53, Mich Talebzadeh wrote: Well as long as it works. Please all check this link from Databricks and let us know your thoughts. Will something similar work for us?. Of course Databricks have much deeper pockets than our ASF community. Will it require moderation in

Re: pyspark - Where are Dataframes created from Python objects stored?

Hi @Mich Talebzadeh , community, Where can I find such insights on the Spark Architecture ? I found few sites below which did/does cover internals : 1. https://github.com/JerryLead/SparkInternals 2. https://books.japila.pl/apache-spark-internals/overview/ 3.

Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

+1 Great initiative. QQ : Stack overflow has a similar feature called "Collectives", but I am not sure of the expenses to create one for Apache Spark. With SO being used ( atleast before ChatGPT became quite the norm for searching questions), it already has a lot of questions asked and answered

Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

+1 . I can contribute to it as well . On Tue, 19 Mar 2024 at 9:19 AM, Code Tutelage wrote: > +1 > > Thanks for proposing > > On Mon, Mar 18, 2024 at 9:25 AM Parsian, Mahmoud > wrote: > >> Good idea. Will be useful >> >> >> >> +1 >> >> >> >> >> >> >> >> *From: *ashok34...@yahoo.com.INVALID >>

[ANNOUNCE] Apache Kyuubi released 1.9.0

Hi all, The Apache Kyuubi community is pleased to announce that Apache Kyuubi 1.9.0 has been released! Apache Kyuubi is a distributed and multi-tenant gateway to provide serverless SQL on data warehouses and lakehouses. Kyuubi provides a pure SQL gateway through Thrift JDBC/ODBC interface for

Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

One very good example is SparkR releases in Conda channel ( https://github.com/conda-forge/r-sparkr-feedstock). This is fully run by the community unofficially. On Tue, 19 Mar 2024 at 09:54, Mich Talebzadeh wrote: > +1 for me > > Mich Talebzadeh, > Dad | Technologist | Solutions Architect |

Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

OK thanks for the update. What does officially blessed signify here? Can we have and run it as a sister site? The reason this comes to my mind is that the interested parties should have easy access to this site (from ISUG Spark sites) as a reference repository. I guess the advice would be that

Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

One of the problem in the past when something like this was brought up was that the ASF couldn't have officially blessed venues beyond the already approved ones. So that's something to look into. Now of course you are welcome to run unofficial things unblessed as long as they follow trademark

Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

Well as long as it works. Please all check this link from Databricks and let us know your thoughts. Will something similar work for us?. Of course Databricks have much deeper pockets than our ASF community. Will it require moderation in our side to block spams and nutcases. Knowledge Sharing Hub

Re: A proposal for creating a Knowledge Sharing Hub for Apache Spark Community

something like this Spark community · GitHub man. 18. mars 2024 kl. 17:26 skrev Parsian, Mahmoud : > Good idea. Will be useful > > > > +1 > > > > > > > > *From: *ashok34...@yahoo.com.INVALID > *Date: *Monday, March 18, 2024 at 6:36 AM > *To: *user @spark ,

  1   2   3   4   5   6   7   8   9   10   >