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Releases: apache/beam

Beam 2.43.0 release

18 Nov 00:58
@chamikaramj chamikaramj
v2.43.0
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chamikaramj Chamikara Jayalath
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Beam 2.43.0 release

We are happy to present the new 2.43.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.43.0, check out the detailed release notes.

Highlights

  • Python 3.10 support in Apache Beam (#21458).
  • An initial implementation of a runner that allows us to run Beam pipelines on Dask. Try it out and give us feedback! (Python) (#18962).

I/Os

  • Decreased TextSource CPU utilization by 2.3x (Java) (#23193).
  • Fixed bug when using SpannerIO with RuntimeValueProvider options (Java) (#22146).
  • Fixed issue for unicode rendering on WriteToBigQuery (#10785)
  • Remove obsolete variants of BigQuery Read and Write, always using Beam-native variant
    (#23564 and #23559).
  • Bumped google-cloud-spanner dependency version to 3.x for Python SDK (#21198).

New Features / Improvements

  • Dataframe wrapper added in Go SDK via Cross-Language (with automatic expansion service). (Go) (#23384).
  • Name all Java threads to aid in debugging (#23049).
  • An initial implementation of a runner that allows us to run Beam pipelines on Dask. (Python) (#18962).
  • Allow configuring GCP OAuth scopes via pipeline options. This unblocks usages of Beam IOs that require additional scopes.
    For example, this feature makes it possible to access Google Drive backed tables in BigQuery (#23290).
  • An example for using Python RunInference from Java (#23290).

Breaking Changes

  • CoGroupByKey transform in Python SDK has changed the output typehint. The typehint component representing grouped values changed from List to Iterable,
    which more accurately reflects the nature of the arbitrarily large output collection. #21556 Beam users may see an error on transforms downstream from CoGroupByKey. Users must change methods expecting a List to expect an Iterable going forward. See document for information and fixes.
  • The PortableRunner for Spark assumes Spark 3 as default Spark major version unless configured otherwise using --spark_version.
    Spark 2 support is deprecated and will be removed soon (#23728).

Bugfixes

  • Fixed Python cross-language JDBC IO Connector cannot read or write rows containing Numeric/Decimal type values (#19817).

List of Contributors

According to git shortlog, the following people contributed to the 2.43.0 release. Thank you to all contributors!

Ahmed Abualsaud
AlexZMLyu
Alexey Romanenko
Anand Inguva
Andrew Pilloud
Andy Ye
Arnout Engelen
Benjamin Gonzalez
Bharath Kumarasubramanian
BjornPrime
Brian Hulette
Bruno Volpato
Chamikara Jayalath
Colin Versteeg
Damon
Daniel Smilkov
Daniela Martín
Danny McCormick
Darkhan Nausharipov
David Huntsperger
Denis Pyshev
Dmitry Repin
Evan Galpin
Evgeny Antyshev
Fernando Morales
Geddy05
Harshit Mehrotra
Iñigo San Jose Visiers
Ismaël Mejía
Israel Herraiz
Jan Lukavský
Juta Staes
Kanishk Karanawat
Kenneth Knowles
KevinGG
Kiley Sok
Liam Miller-Cushon
Luke Cwik
Mc
Melissa Pashniak
Moritz Mack
Ning Kang
Pablo Estrada
Philippe Moussalli
Pranav Bhandari
Rebecca Szper
Reuven Lax
Ritesh Ghorse
Robert Bradshaw
Robert Burke
Ryan Thompson
Ryohei Nagao
Sam Rohde
Sam Whittle
Sanil Jain
Seunghwan Hong
Shane Hansen
Shubham Krishna
Shunsuke Otani
Steve Niemitz
Steven van Rossum
Svetak Sundhar
Thiago Nunes
Toran Sahu
Veronica Wasson
Vitaly Terentyev
Vladislav Chunikhin
Xinyu Liu
Yi Hu
Yixiao Shen
alexeyinkin
arne-alex
azhurkevich
bulat safiullin
bullet03
coldWater
dpcollins-google
egalpin
johnjcasey
liferoad
rvballada
shaojwu
tvalentyn

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Contributors

raboof, thiagotnunes, and 75 other contributors
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Beam 2.42.0 release

17 Oct 16:22
@lostluck lostluck
v2.42.0
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Beam 2.42.0 release

We are happy to present the new 2.42.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.42.0, check out the detailed release notes.

Highlights

  • Added support for stateful DoFns to the Go SDK.

New Features / Improvements

  • Added support for Zstd compression to the Python SDK.
  • Added support for Google Cloud Profiler to the Go SDK.
  • Added support for stateful DoFns to the Go SDK.

Breaking Changes

  • The Go SDK's Row Coder now uses a different single-precision float encoding for float32 types to match Java's behavior (#22629).

Bugfixes

  • Fixed Python cross-language JDBC IO Connector cannot read or write rows containing Timestamp type values 19817.

Known Issues

  • Go SDK doesn't yet support Slowly Changing Side Input pattern (#23106)
  • See a full list of open issues that affect this version.

What's Changed

Read more

Contributors

masahitojp, ihji, and 66 other contributors
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Beam 2.41.0 release

23 Aug 19:07
@kileys kileys
v2.41.0
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Beam 2.41.0 release

We are happy to present the new 2.41.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.41.0, check out the detailed release notes.

I/Os

  • Projection Pushdown optimizer is now on by default for streaming, matching the behavior of batch pipelines since 2.38.0. If you encounter a bug with the optimizer, please file an issue and disable the optimizer using pipeline option --experiments=disable_projection_pushdown.

New Features / Improvements

  • Previously available in Java sdk, Python sdk now also supports logging level overrides per module. (#18222).

Breaking Changes

  • Projection Pushdown optimizer may break Dataflow upgrade compatibility for optimized pipelines when it removes unused fields. If you need to upgrade and encounter a compatibility issue, disable the optimizer using pipeline option --experiments=disable_projection_pushdown.

Deprecations

  • Support for Spark 2.4.x is deprecated and will be dropped with the release of Beam 2.44.0 or soon after (Spark runner) (#22094).
  • The modules amazon-web-services and
    kinesis for AWS Java SDK v1 are deprecated
    in favor of amazon-web-services2
    and will be eventually removed after a few Beam releases (Java) (#21249).

Bugfixes

  • Fixed a condition where retrying queries would yield an incorrect cursor in the Java SDK Firestore Connector (#22089).
  • Fixed plumbing allowed lateness in Go SDK. It was ignoring the user set value earlier and always used to set to 0. (#22474).

Known Issues

List of Contributors

According to git shortlog, the following people contributed to the 2.41.0 release. Thank you to all contributors!

Ahmed Abualsaud
Ahmet Altay
akashorabek
Alexey Inkin
Alexey Romanenko
Anand Inguva
andoni-guzman
Andrew Pilloud
Andrey
Andy Ye
Balázs Németh
Benjamin Gonzalez
BjornPrime
Brian Hulette
bulat safiullin
bullet03
Byron Ellis
Chamikara Jayalath
Damon Douglas
Daniel Oliveira
Daniel Thevessen
Danny McCormick
David Huntsperger
Dheeraj Gharde
Etienne Chauchot
Evan Galpin
Fernando Morales
Heejong Lee
Jack McCluskey
johnjcasey
Kenneth Knowles
Ke Wu
Kiley Sok
Liam Miller-Cushon
Lucas Nogueira
Luke Cwik
MakarkinSAkvelon
Manu Zhang
Minbo Bae
Moritz Mack
Naireen Hussain
Ning Kang
Oleh Borysevych
Pablo Estrada
pablo rodriguez defino
Pranav Bhandari
Rebecca Szper
Red Daly
Reuven Lax
Ritesh Ghorse
Robert Bradshaw
Robert Burke
Ryan Thompson
Sam Whittle
Steven Niemitz
Valentyn Tymofieiev
Vincent Marquez
Vitaly Terentyev
Vlad
Vladislav Chunikhin
Yichi Zhang
Yi Hu
yirutang
Yixiao Shen
Yu Feng

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v2.40.0

23 Jun 16:01
@pabloem pabloem
v2.40.0
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v2.40.0

We are happy to present the new 2.40.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this
release.

For more information on changes in 2.40.0 check out the detailed release notes.

Highlights

  • Added RunInference API, a framework agnostic transform for inference. With this release, PyTorch and Scikit-learn are supported by the transform.
    See also example at apache_beam/examples/inference/pytorch_image_classification.py

I/Os

  • Upgraded to Hive 3.1.3 for HCatalogIO. Users can still provide their own version of Hive. (Java) (Issue-19554).

New Features / Improvements

  • Go SDK users can now use generic registration functions to optimize their DoFn execution. (BEAM-14347)
  • Go SDK users may now write self-checkpointing Splittable DoFns to read from streaming sources. (BEAM-11104)
  • Go SDK textio Reads have been moved to Splittable DoFns exclusively. (BEAM-14489)
  • Pipeline drain support added for Go SDK has now been tested. (BEAM-11106)
  • Go SDK users can now see heap usage, sideinput cache stats, and active process bundle stats in Worker Status. (BEAM-13829)
  • The serialization (pickling) library for Python is dill==0.3.1.1 (BEAM-11167)

Breaking Changes

  • The Go Sdk now requires a minimum version of 1.18 in order to support generics (BEAM-14347).
  • synthetic.SourceConfig field types have changed to int64 from int for better compatibility with Flink's use of Logical types in Schemas (Go) (BEAM-14173)
  • Default coder updated to compress sources used with BoundedSourceAsSDFWrapperFn and UnboundedSourceAsSDFWrapper.

Bugfixes

  • Fixed X (Java/Python) (BEAM-X).
  • Fixed Java expansion service to allow specific files to stage (BEAM-14160).
  • Fixed Elasticsearch connection when using both ssl and username/password (Java) (BEAM-14000)

Detailed list of PRs

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Contributors

masahitojp, ihji, and 69 other contributors
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Beam 2.39.0 release

25 May 18:47
@y1chi y1chi
v2.39.0
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Beam 2.39.0 release

We are happy to present the new 2.39.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this
release.

For more information on changes in 2.39.0 check out the detailed release notes.

I/Os

  • JmsIO gains the ability to map any kind of input to any subclass of javax.jms.Message (Java) (BEAM-16308).
  • JmsIO introduces the ability to write to dynamic topics (Java) (BEAM-16308).
    • A topicNameMapper must be set to extract the topic name from the input value.
    • A valueMapper must be set to convert the input value to JMS message.
  • Reduce number of threads spawned by BigqueryIO StreamingInserts (
    BEAM-14283).
  • Implemented Apache PulsarIO (BEAM-8218).

New Features / Improvements

  • Support for flink scala 2.12, because most of the libraries support version 2.12 onwards. (beam-14386)
  • 'Manage Clusters' JupyterLab extension added for users to configure usage of Dataproc clusters managed by Interactive Beam (Python) (BEAM-14130).
  • Pipeline drain support added for Go SDK (BEAM-11106). Note: this feature is not yet fully validated and should be treated as experimental in this release.
  • DataFrame.unstack(), DataFrame.pivot() and Series.unstack()
    implemented for DataFrame API (BEAM-13948, BEAM-13966).
  • Support for impersonation credentials added to dataflow runner in the Java and Python SDK (BEAM-14014).
  • Implemented Jupyterlab extension for managing Dataproc clusters (BEAM-14130).
  • ExternalPythonTransform API added for easily invoking Python transforms from
    Java (BEAM-14143).
  • Added Add support for Elasticsearch 8.x (BEAM-14003).
  • Shard aware Kinesis record aggregation (AWS Sdk v2), (BEAM-14104).
  • Upgrade to ZetaSQL 2022.04.1 (BEAM-14348).
  • Fixed ReadFromBigQuery cannot be used with the interactive runner (BEAM-14112).

Breaking Changes

  • Unused functions ShallowCloneParDoPayload(), ShallowCloneSideInput(), and ShallowCloneFunctionSpec() have been removed from the Go SDK's pipelinex package (BEAM-13739).
  • JmsIO requires an explicit valueMapper to be set (BEAM-16308). You can use the TextMessageMapper to convert String inputs to JMS TestMessages:
  JmsIO.<String>write()
        .withConnectionFactory(jmsConnectionFactory)
        .withValueMapper(new TextMessageMapper());
  • Coders in Python are expected to inherit from Coder. (BEAM-14351).
  • New abstract method metadata() added to io.filesystem.FileSystem in the
    Python SDK. (BEAM-14314)

Deprecations

Bugfixes

  • Fixed Java Spanner IO NPE when ProjectID not specified in template executions (Java) (BEAM-14405).
  • Fixed potential NPE in BigQueryServicesImpl.getErrorInfo (Java) (BEAM-14133).

Known Issues

List of Contributors

According to git shortlog, the following people contributed to the 2.39.0 release. Thank you to all contributors!

Ahmed Abualsaud,
Ahmet Altay,
Aizhamal Nurmamat kyzy,
Alexander Zhuravlev,
Alexey Romanenko,
Anand Inguva,
Andrei Gurau,
Andrew Pilloud,
Andy Ye,
Arun Pandian,
Arwin Tio,
Aydar Farrakhov,
Aydar Zainutdinov,
AydarZaynutdinov,
Balázs Németh,
Benjamin Gonzalez,
Brian Hulette,
Buqian Zheng,
Chamikara Jayalath,
Chun Yang,
Daniel Oliveira,
Daniela Martín,
Danny McCormick,
David Huntsperger,
Deepak Nagaraj,
Denise Case,
Esun Kim,
Etienne Chauchot,
Evan Galpin,
Hector Miuler Malpica Gallegos,
Heejong Lee,
Hengfeng Li,
Ilango Rajagopal,
Ilion Beyst,
Israel Herraiz,
Jack McCluskey,
Kamil Bregula,
Kamil Breguła,
Ke Wu,
Kenneth Knowles,
KevinGG,
Kiley,
Kiley Sok,
Kyle Weaver,
Liam Miller-Cushon,
Luke Cwik,
Marco Robles,
Matt Casters,
Michael Li,
MiguelAnzoWizeline,
Milan Patel,
Minbo Bae,
Moritz Mack,
Nick Caballero,
Niel Markwick,
Ning Kang,
Oskar Firlej,
Pablo Estrada,
Pavel Avilov,
Reuven Lax,
Reza Rokni,
Ritesh Ghorse,
Robert Bradshaw,
Robert Burke,
Ryan Thompson,
Sam Whittle,
Steven Niemitz,
Thiago Nunes,
Tomo Suzuki,
Valentyn Tymofieiev,
Victor,
Yi Hu,
Yichi Zhang,
Yiru Tang,
ahmedabu98,
andoni-guzman,
brachipa,
bulat safiullin,
bullet03,
dannymartinm,
daria.malkova,
dpcollins-google,
egalpin,
emily,
fbeevikm,
johnjcasey,
kileys,
[email protected],
nguyennk92,
pablo rodriguez defino,
rszper,
rvballada,
sachinag,
tvalentyn,
vachan-shetty,
yirutang

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Beam 2.38.0 release

20 Apr 23:03
@youngoli youngoli
v2.38.0
93fd177
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Beam 2.38.0 release

We are happy to present the new 2.38.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.38.0 check out the detailed release notes.

I/Os

  • Introduce projection pushdown optimizer to the Java SDK (BEAM-12976). The optimizer currently only works on the BigQuery Storage API, but more I/Os will be added in future releases. If you encounter a bug with the optimizer, please file a JIRA and disable the optimizer using pipeline option --experiments=disable_projection_pushdown.
  • A new IO for Neo4j graph databases was added. (BEAM-1857) It has the ability to update nodes and relationships using UNWIND statements and to read data using cypher statements with parameters.
  • amazon-web-services2 has reached feature parity and is finally recommended over the earlier amazon-web-services and kinesis modules (Java). These will be deprecated in one of the next releases (BEAM-13174).

New Features / Improvements

  • Pipeline dependencies supplied through --requirements_file will now be staged to the runner using binary distributions (wheels) of the PyPI packages for linux_x86_64 platform (BEAM-4032). To restore the behavior to use source distributions, set pipeline option --requirements_cache_only_sources. To skip staging the packages at submission time, set pipeline option --requirements_cache=skip (Python).
  • The Flink runner now supports Flink 1.14.x (BEAM-13106).
  • Interactive Beam now supports remotely executing Flink pipelines on Dataproc (Python) (BEAM-14071).

Breaking Changes

  • (Python) Previously DoFn.infer_output_types was expected to return Iterable[element_type] where element_type is the PCollection elemnt type. It is now expected to return element_type. Take care if you have overriden infer_output_type in a DoFn (this is not common). See BEAM-13860.
  • (amazon-web-services2) The types of awsRegion / endpoint in AwsOptions changed from String to Region / URI (BEAM-13563).

Deprecations

  • Beam 2.38.0 will be the last minor release to support Flink 1.11.
  • (amazon-web-services2) Client providers (withXYZClientProvider()) as well as IO specific RetryConfigurations are deprecated, instead use withClientConfiguration() or AwsOptions to configure AWS IOs / clients.
    Custom implementations of client providers shall be replaced with a respective ClientBuilderFactory and configured through AwsOptions (BEAM-13563).

Bugfixes

  • Fix S3 copy for large objects (Java) (BEAM-14011)
  • Fix quadratic behavior of pipeline canonicalization (Go) (BEAM-14128)
    • This caused unnecessarily long pre-processing times before job submission for large complex pipelines.
  • Fix pyarrow version parsing (Python)(BEAM-14235)

Known Issues

List of Contributors

According to git shortlog, the following people contributed to the 2.38.0 release. Thank you to all contributors!

abhijeet-lele
Ahmet Altay
akustov
Alexander
Alexander Zhuravlev
Alexey Romanenko
AlikRodriguez
Anand Inguva
andoni-guzman
andreukus
Andy Ye
Ankur Goenka
ansh0l
Artur Khanin
Aydar Farrakhov
Aydar Zainutdinov
Benjamin Gonzalez
Brian Hulette
brucearctor
bulat safiullin
bullet03
Carl Mastrangelo
Chamikara Jayalath
Chun Yang
Daniela Martín
Daniel Oliveira
Danny McCormick
daria.malkova
David Cavazos
David Huntsperger
dmitryor
Dmytro Sadovnychyi
dpcollins-google
egalpin
Elias Segundo Antonio
emily
Etienne Chauchot
Hengfeng Li
Ismaël Mejía
Israel Herraiz
Jack McCluskey
Jakub Kukul
Janek Bevendorff
Jeff Klukas
Johan Sternby
Kamil Breguła
Kenneth Knowles
Ke Wu
Kiley
Kyle Weaver
laraschmidt
Lara Schmidt
LE QUELLEC Olivier
Luka Kalinovcic
Luke Cwik
Marcin Kuthan
masahitojp
Masato Nakamura
Matt Casters
Melissa Pashniak
Michael Li
Miguel Hernandez
Moritz Mack
mosche
nancyxu123
Nathan J Mehl
Niel Markwick
Ning Kang
Pablo Estrada
paul-tlh
Pavel Avilov
Rahul Iyer
Reuven Lax
Ritesh Ghorse
Robert Bradshaw
Robert Burke
Ryan Skraba
Ryan Thompson
Sam Whittle
Seth Vargo
sp029619
Steven Niemitz
Thiago Nunes
Udi Meiri
Valentyn Tymofieiev
Victor
vitaly.terentyev
Yichi Zhang
Yi Hu
yirutang
Zachary Houfek
Zoe

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Beam 2.37.0 release

04 Mar 19:21
@TheNeuralBit TheNeuralBit
v2.37.0
d97c521
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Beam 2.37.0 release

We are happy to present the new 2.37.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.37.0 check out the detailed release notes.

Highlights

  • Java 17 support for Dataflow (BEAM-12240).
    • Users using Dataflow Runner V2 may see issues with state cache due to inaccurate object sizes (BEAM-13695).
    • ZetaSql is currently unsupported (issue).
  • Python 3.9 support in Apache Beam (BEAM-12000).
    • Dataflow support for Python 3.9 is expected to be available with 2.37.0,
      but may not be fully available yet when the release is announced (BEAM-13864).
    • Users of Dataflow Runner V2 can run Python 3.9 pipelines with 2.37.0 release right away.

I/Os

  • Go SDK now has wrappers for the following Cross Language Transforms from Java, along with automatic expansion service startup for each.

New Features / Improvements

  • DataFrame API now supports pandas 1.4.x (BEAM-13605).
  • Go SDK DoFns can now observe trigger panes directly (BEAM-13757).

Known Issues

List of Contributors

According to git shortlog, the following people contributed to the 2.37.0 release. Thank you to all contributors!

Aizhamal Nurmamat kyzy
Alexander
Alexander Chermenin
Alexandr Zhuravlev
Alexey Romanenko
Anand Inguva
andoni-guzman
andreukus
Andy Ye
Artur Khanin
Aydar Farrakhov
Aydar Zainutdinov
AydarZaynutdinov
Benjamin Gonzalez
Brian Hulette
Chamikara Jayalath
Daniel Oliveira
Danny McCormick
daria-malkova
daria.malkova
darshan-sj
David Huntsperger
dprieto91
emily
Etienne Chauchot
Fernando Morales
Heejong Lee
Ismaël Mejía
Jack McCluskey
Jan Lukavský
johnjcasey
Kamil Breguła
kellen
Kenneth Knowles
kileys
Kyle Weaver
Luke Cwik
Marcin Kuthan
Marco Robles
Matt Rudary
Miguel Hernandez
Milena Bukal
Moritz Mack
Mostafa Aghajani
Ning Kang
Pablo Estrada
Pavel Avilov
Reuven Lax
Ritesh Ghorse
Robert Bradshaw
Robert Burke
Sam Whittle
Sandy Chapman
Sergey Kalinin
Thiago Nunes
thorbjorn444
Tim Robertson
Tomo Suzuki
Valentyn Tymofieiev
Victor
Victor Chen
Vitaly Ivanov
Yichi Zhang

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Beam 2.36.0 release

08 Feb 00:08
@emilymye emilymye
v2.36.0
81f3a16
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Beam 2.36.0 release

We are happy to present the new 2.36.0 release of Apache Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.36.0, check out the detailed release
notes.

I/Os

  • Support for stopReadTime on KafkaIO SDF (Java).(BEAM-13171).

New Features / Improvements

  • Added support for cloudpickle as a pickling library for Python SDK (BEAM-8123). To use cloudpickle, set pipeline option: --pickler_lib=cloudpickle
  • Added option to specify triggering frequency when streaming to BigQuery (Python) (BEAM-12865).
  • Added option to enable caching uploaded artifacts across job runs for Python Dataflow jobs (BEAM-13459). To enable, set pipeline option: --enable_artifact_caching, this will be enabled by default in a future release.

Breaking Changes

  • Updated the jedis from 3.x to 4.x to Java RedisIO. If you are using RedisIO and using jedis directly, please refer to this page to update it. (BEAM-12092).
  • Datatype of timestamp fields in SqsMessage for AWS IOs for SDK v2 was changed from String to long, visibility of all fields was fixed from package private to public BEAM-13638.
  • Properly check output timestamps on elements output from DoFns, timers, and onWindowExpiration in Java BEAM-12931.
  • Fixed a bug with DeferredDataFrame.xs when used with a non-tuple key
    (BEAM-13421).

Known Issues

  • Users may encounter an unexpected java.lang.ArithmeticException when outputting a timestamp
    for an element further than allowedSkew from an allowed DoFN skew set to a value more than
    Integer.MAX_VALUE.
  • See a full list of open issues that affect this version.

List of Contributors

According to git shortlog, the following people contributed to the 2.36.0 release. Thank you to all contributors!

Ada Wong
Ahmet Altay
Alexander
Alexander Dahl
Alexandr Zhuravlev
Alexey Romanenko
AlikRodriguez
Anand Inguva
Andrew Pilloud
Andy Ye
Arkadiusz Gasiński
Artur Khanin
Arun Pandian
Aydar Farrakhov
Aydar Zainutdinov
AydarZaynutdinov
Benjamin Gonzalez
Brian Hulette
Chamikara Jayalath
Daniel Collins
Daniel Oliveira
Daniel Thevessen
Daniela Martín
David Hinkes
David Huntsperger
Emily Ye
Etienne Chauchot
Evan Galpin
Heejong Lee
Ilya
Ilya Kozyrev
In-Ho Yi
Jack McCluskey
Janek Bevendorff
Jarek Potiuk
Ke Wu
KevinGG
Kyle Hersey
Kyle Weaver
Luís Bianchin
Luke Cwik
Masato Nakamura
Matthias Baetens
Mehdi Drissi
Melissa Pashniak
Michel Davit
Miguel Hernandez
MiguelAnzoWizeline
Milena Bukal
Moritz Mack
Mostafa Aghajani
Nathan J Mehl
Niel Markwick
Ning Kang
Pablo Estrada
Pavel Avilov
Quentin Sommer
Reuben van Ammers
Reuven Lax
Ritesh Ghorse
Robert Bradshaw
Robert Burke
Ryan Thompson
Sam Whittle
Sayat
Sergei Lebedev
Sergey Kalinin
Steve Niemitz
Talat Uyarer
Thiago Nunes
Tianyang Hu
Tim Robertson
Valentyn Tymofieiev
Vitaly Ivanov
Yichi Zhang
Yiru Tang
Yu Feng
Yu ISHIKAWA
Zachary Houfek
blais
daria-malkova
daria.malkova
darshan-sj
dpcollins-google
emily
ewianda
johnjcasey
kileys
lam206
laraschmidt
mosche
[email protected]
tvalentyn

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Beam 2.35.0 release

30 Dec 02:00
@tvalentyn tvalentyn
v2.35.0
a3400e3
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Beam 2.35.0 release

We are happy to present the new 2.35.0 release of Apache Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.35.0, check out the detailed release
notes.

Highlights

  • MultiMap side inputs are now supported by the Go SDK (BEAM-3293).
  • Side inputs are supported within Splittable DoFns for Dataflow Runner V1 and Dataflow Runner V2. (BEAM-12522).
  • Upgrades Log4j version used in test suites (Apache Beam testing environment only, not for end user consumption) to 2.17.0(BEAM-13434).
    Note that Apache Beam versions do not depend on the Log4j 2 dependency (log4j-core) impacted by CVE-2021-44228.
    However we urge users to update direct and indirect dependencies (if any) on Log4j 2 to the latest version by updating their build configuration and redeploying impacted pipelines.

I/Os

  • We changed the data type for ranges in JdbcIO.readWithPartitions from int to long (BEAM-13149).
    This is a relatively minor breaking change, which we're implementing to improve the usability of the transform without increasing cruft.
    This transform is relatively new, so we may implement other breaking changes in the future to improve its usability.
  • Side inputs are supported within Splittable DoFns for Dataflow Runner V1 and Dataflow Runner V2. (BEAM-12522).

New Features / Improvements

  • Added custom delimiters to Python TextIO reads (BEAM-12730).
  • Added escapechar parameter to Python TextIO reads (BEAM-13189).
  • Splittable reading is enabled by default while reading data with ParquetIO (BEAM-12070).
  • DoFn Execution Time metrics added to Go (BEAM-13001).
  • Cross-bundle side input caching is now available in the Go SDK for runners that support the feature by setting the EnableSideInputCache hook (BEAM-11097).
  • Upgraded the GCP Libraries BOM version to 24.0.0 and associated dependencies (BEAM-11205). For Google Cloud client library versions set by this BOM,
    see this table.
  • Removed avro-python3 dependency in AvroIO. Fastavro has already been our Avro library of choice on Python 3. Boolean use_fastavro is left for api compatibility, but will have no effect.(BEAM-13016).
  • MultiMap side inputs are now supported by the Go SDK (BEAM-3293).
  • Remote packages can now be downloaded from locations supported by apache_beam.io.filesystems. The files will be downloaded on Stager and uploaded to staging location. For more information, see BEAM-11275

Breaking Changes

  • A new URN convention was adopted for cross-language transforms and existing URNs were updated. This may break advanced use-cases, for example, if a custom expansion service is used to connect diffrent Beam Java and Python versions. (BEAM-12047).
  • The upgrade to Calcite 1.28.0 introduces a breaking change in the SUBSTRING function in SqlTransform, when used with the Calcite dialect (BEAM-13099, CALCITE-4427).
  • ListShards (with DescribeStreamSummary) is used instead of DescribeStream to list shards in Kinesis streams (AWS SDK v2). Due to this change, as mentioned in AWS documentation, for fine-grained IAM policies it is required to update them to allow calls to ListShards and DescribeStreamSummary APIs. For more information, see Controlling Access to Amazon Kinesis Data Streams (BEAM-13233).

Deprecations

  • Non-splittable reading is deprecated while reading data with ParquetIO (BEAM-12070).

Bugfixes

  • Properly map main input windows to side input windows by default (Go)
    (BEAM-11087).
  • Fixed data loss when writing to DynamoDB without setting deduplication key names (Java)
    (BEAM-13009).
  • Go SDK Examples now have types and functions registered. (Go) (BEAM-5378)

Known Issues

  • Users of beam-sdks-java-io-hcatalog (and beam-sdks-java-extensions-sql-hcatalog) must take care to override the transitive log4j dependency when they add a hive dependency (BEAM-13499).

List of Contributors

According to git shortlog, the following people contributed to the 2.35.0 release. Thank you to all contributors!

Ahmet Altay
Alexandr Zhuravlev
Alexey Romanenko
AlikRodriguez
Anand Inguva
Andrew Pilloud
Ankur Goenka
Anthony Sottile
Artur Khanin
Aydar Farrakhov
Aydar Zainutdinov
Benjamin Gonzalez
brachipa
Brian Hulette
Calvin Leung
Chamikara Jayalath
Chris Gray
Damon Douglas
Daniel Collins
Daniel Oliveira
daria.malkova
darshan-sj
David Huntsperger
Dmitrii Kuzin
dpcollins-google
dprieto
egalpin
Etienne Chauchot
Eugene Nikolaiev
Fernando Morales
Hector Lagos
Heejong Lee
Ilya Kozyrev
Iñigo San Jose Visiers
Jack McCluskey
Jiayang Wu
jrhy
Kenneth Knowles
KevinGG
kileys
klmilam
Kyle Weaver
Luís Bianchin
Luke Cwik
Melissa Pashniak
Michael Luckey
Miguel Hernandez
Milena Bukal
Minbo Bae
minherz
Moritz Mack
mosche
Natalie
Ning Kang
Pablo Estrada
Pavel Avilov
Reuven Lax
Ritesh Ghorse
Robert Bradshaw
Robert Burke
Rogan Morrow
Ruslan Altynnikov
Sam Whittle
Sergey Kalinin
Slava Chernyak
Svetak Sundhar
Tianyang Hu
Tim Robertson
Tomo Suzuki
tuorhador
Udi Meiri
vachan-shetty
Valentyn Tymofieiev
Yichi Zhang
zhoufek

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Beam 2.34.0 release

11 Nov 20:03
@ibzib ibzib
v2.34.0
b3b1843
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Beam 2.34.0 release

We are happy to present the new 2.34.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.34.0, check out the detailed release
notes.

Highlights

  • The Beam Java API for Calcite SqlTransform is no longer experimental (BEAM-12680).
  • Python's ParDo (Map, FlatMap, etc.) transforms now suport a with_exception_handling option for easily ignoring bad records and implementing the dead letter pattern.

I/Os

  • ReadFromBigQuery and ReadAllFromBigQuery now run queries with BATCH priority by default. The query_priority parameter is introduced to the same transforms to allow configuring the query priority (Python) (BEAM-12913).
  • [EXPERIMENTAL] Support for BigQuery Storage Read API added to ReadFromBigQuery. The newly introduced method parameter can be set as DIRECT_READ to use the Storage Read API. The default is EXPORT which invokes a BigQuery export request. (Python) (BEAM-10917).
  • [EXPERIMENTAL] Added use_native_datetime parameter to ReadFromBigQuery to configure the return type of DATETIME fields when using ReadFromBigQuery. This parameter can only be used when method = DIRECT_READ(Python) (BEAM-10917).

New Features / Improvements

  • Upgrade to Calcite 1.26.0 (BEAM-9379).
  • Added a new dataframe extra to the Python SDK that tracks pandas versions
    we've verified compatibility with. We now recommend installing Beam with pip install apache-beam[dataframe] when you intend to use the DataFrame API
    (BEAM-12906).
  • Add an example of deploying Python Apache Beam job with Spark Cluster

Breaking Changes

  • SQL Rows are no longer flattened (BEAM-5505).
  • [Go SDK] beam.TryCrossLanguage's signature now matches beam.CrossLanguage. Like other Try functions it returns an error instead of panicking. (BEAM-9918).
  • BEAM-12925 was fixed. It used to silently pass incorrect null data read from JdbcIO. Pipelines affected by this will now start throwing failures instead of silently passing incorrect data.

Bugfixes

  • Fixed error while writing multiple DeferredFrames to csv (Python) (BEAM-12701).
  • Fixed error when importing the DataFrame API with pandas 1.0.x installed (BEAM-12945).
  • Fixed top.SmallestPerKey implementation in the Go SDK (BEAM-12946).

List of Contributors

According to git shortlog, the following people contributed to the 2.34.0 release. Thank you to all contributors!

Ahmet Altay,
Aizhamal Nurmamat kyzy,
Alex Amato,
Alexander Chermenin,
Alexey Romanenko,
AlikRodriguez,
Andrew Pilloud,
Andy Xu,
Ankur Goenka,
Aydar Farrakhov,
Aydar Zainutdinov,
Aydar Zaynutdinov,
AydarZaynutdinov,
Benjamin Gonzalez,
BenWhitehead,
Brachi Packter,
Brian Hulette,
Bu Sun Kim,
Chamikara Jayalath,
Chris Gray,
Chuck Yang,
Chun Yang,
Claire McGinty,
comet,
Daniel Collins,
Daniel Oliveira,
Daniel Thevessen,
daria.malkova,
David Cavazos,
David Huntsperger,
Dmytro Kozhevin,
dpcollins-google,
Eduardo Sánchez López,
Elias Djurfeldt,
emily,
Emily Ye,
Enis Sert,
Etienne Chauchot,
Fernando Morales,
Heejong Lee,
Ihor Indyk,
Ismaël Mejía,
Israel Herraiz,
Jack McCluskey,
Jonathan Hourany,
Judah Rand,
Kenneth Knowles,
KevinGG,
Ke Wu,
kileys,
Kyle Weaver,
Luke Cwik,
masahitojp,
MiguelAnzoWizeline,
Minbo Bae,
Niels Basjes,
Ning Kang,
Pablo Estrada,
pareshsarafmdb,
Paul Féraud,
Piotr Szczepanik,
Reuven Lax,
Ritesh Ghorse,
R. Miles McCain,
Robert Bradshaw,
Robert Burke,
Rogan Morrow,
Ruwan Lambrichts,
rvballada,
Ryan Thompson,
Sam Rohde,
Sam Whittle,
Ștefan Istrate,
Steve Niemitz,
Thomas Li Fredriksen,
Tomo Suzuki,
tvalentyn,
Udi Meiri,
Vachan,
Valentyn Tymofieiev,
Vincent Marquez,
WinsonT,
Yichi Zhang,
Yifan Mai,
Yilei "Dolee" Yang,
zhoufek

Assets 2
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