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Yandex Data Processing image release notes

Written by
Updated at March 28, 2025

For a complete list of current and deprecated Yandex Data Processing images, see Runtime environment.

2.2.x images (beta)

2.2.7 (beta)

  • Upgraded to Java 11.

2.2.6 (beta)

  • Fixed an error where the dataproc:nodemanager_available_memory_ratio property was ignored when reserving a memory share for YARN NodeManager.

2.2.5 (beta)

  • The following components were updated:

    • Hadoop to 3.3.2
    • Spark to 3.5.0

  • Python upgraded to version 3.11.10.

  • The following libraries were updated:

    • IPython to 8.22.0
    • ipykernel to 6.29.5
    • Matplotlib to 3.9.2
    • pandas to 2.2.2
    • PyArrow to 14.0.2
    • scikit-learn to 1.5.1

2.1.x images

2.1.19

  • Fixed an error where the dataproc:nodemanager_available_memory_ratio property was ignored when reserving a memory share for YARN NodeManager.

2.1.18

  • Updated Conda and changed the default solver to Mamba.
  • Added logging during Conda package installation.
  • Deleted [ERROR] can't parse line lines from cluster startup logs.

2.1.17

  • Enabled publishing Resource Manager events in Job History Server by default.

2.1.16

  • Added rotation of Yarn Timelinserver logs.

2.1.15

  • Stabilized the 2.1 image line.

  • Implemented deletion of properties from configuration files when deleting them from the cluster configuration.

  • The following components were updated:

    • Hadoop to 3.3.2
    • Livy to 0.8.0
    • Spark to 3.3.2
    • Tez to 0.10.1
    • Zeppelin to 0.10.1

  • Deprecated components were removed:

    • HBase
    • Hive
    • Zookeeper
    • Oozie

  • Python updated to version 3.8.13.

  • The following libraries were updated:

    • IPython to 7.22.0
    • ipykernel to 5.3.4
    • Matplotlib to 3.4.2
    • pandas to 1.2.4
    • PyArrow to 14.0.2
    • scikit-learn to 0.24.1

Image 2.0.x

2.0.78

  • Fixed an error where the dataproc:nodemanager_available_memory_ratio property was ignored when reserving a memory share for YARN NodeManager.

2.0.77

  • Added logging during Conda package installation.
  • Deleted [ERROR] can't parse line lines from cluster startup logs.

2.0.76

  • Added rotation of Yarn Timelinserver logs.

2.0.74

  • Implemented deletion of properties from configuration files when deleting them from the cluster configuration.

2.0.69

  • Added the kafka-clients and commons-pool2 libraries required for Apache Spark™ and Apache Kafka® integration.

2.0.66

  • Fixed the issue when YARN NodeManager was run on a new host before the initialization scripts were executed.

2.0.64

  • Added support for Helium.
  • Fixed the issue with redundant decommission.
  • Log delivery to Cloud Logging is run once a node is started.

2.0.62

  • Fixed an error when the Zeppelin default plugins were missing.
  • Fixed an issue when Hive job errors were handled incorrectly.

2.0.61

  • Internal changes.

2.0.59

  • Added support for Spark and MapReduce services in a single-host cluster.

2.0.58

  • Added the ability to keep user-defined properties of the Zeppelin interpreter when restarting a cluster. The spark.submit.deployMode, spark.driver.cores, spark.driver.memory, spark.executor.cores, spark.executor.memory, spark.files, spark.jars, and spark.jars.packages properties are not saved: they are rewritten from Spark properties.

2.0.56

  • Optimized requests to the metadata service when interacting with s3.

2.0.55

  • Improved logging in the initialization scripts.

2.0.54

  • Fixed errors in the TEZ component configuration.

2.0.53

  • Fixed the error with cores/memory configuration for Spark/Yarn when specifying the spark:spark.submit.deployMode cluster property.
  • Fixed the spark-defaults.yaml configuration file update when updating the cluster properties.

2.0.52

  • Added a script to hosts for adjusting the initialization script status manually.

2.0.50

  • The execution results of user scenarios now go to masternode by default.

2.0.49

  • Fixed an error when user-defined settings were ignored in Hive Metastore Server.

2.0.48

2.0.47

  • Corrected a TCP session leak with the metadata service on high-load clusters. The leak could have resulted in an IAM token not updating for authorization in Object Storage and other services.
  • Fixed the YandexMetadataCredentialsProvider does not implement AWSCredentialsProvider error that prevented Hive Metastore tables from loading.

2.0.46

  • Some Spark properties are now used in Zeppelin as well, e.g., spark.submit.deployMode, spark.driver.cores, spark.driver.memory, spark.executor.cores, spark.executor.memory, spark.files, spark.jars, and spark.jars.packages.

2.0.45

  • Fixed an error with the MapReduce Application History Server not being hosted on the cluster master host.
  • Enabled the HIVE configuration without YARN.
  • Allowed running HiveServer2 with MapReduce only.

2.0.43

  • Unified cores/memory calculations for Spark/YARN.

2.0.42

  • Upgraded Apache Spark to version 3.0.3 and built it with the hadoop-cloud profile to use Magic Committer and Parquet format.
  • Fixed an error where the hive.metastore.uris settings for Spark were ignored when using an external Hive metastore.

2.0.41

  • Added hive-site.xml to classpath for Spark apps.
  • Fixed an error when system Python was used instead of a Conda environment while running PySpark.

2.0.40

  • Fixed an error when user scenarios failed to run.

2.0.39

  • Added support for lightweight clusters (without HDFS and data storage subclusters).

2.0.38

  • Adapted images to be used in subnets with a user-defined DNS zone.

2.0.37

  • Added the YC CLI to PATH for initialization scripts.

2.0.36

  • The YC CLI is installed on all cluster hosts by default.
  • Added the following values to environment variables for initialization scripts: CLUSTER_ID, S3_BUCKET, ROLE, CLUSTER_SERVICES, MIN_WORKER_COUNT, and MAX_WORKER_COUNT.

2.0.35

  • Added support for cluster initialization scripts.

2.0

  • The following components were updated:

    • HBase to 2.2.7
    • Hadoop to 3.2.2
    • Hive to 3.1.2
    • Livy to 0.8.0
    • Oozie to 5.2.1
    • Spark to 3.0.2
    • Tez to 0.10.0
    • Zeppelin to 0.9.0

  • Deprecated components have been removed:

    • Flume
    • Sqoop

  • Python updated to version 3.8.10.

  • The following libraries were updated:

    • IPython to 7.19.0
    • ipykernel to 5.3.4
    • Matplotlib to 3.2.2
    • pandas to 1.1.3
    • PyArrow to 1.0.1
    • PyHive to 0.6.1
    • scikit-learn to 0.23.2

  • The following libraries were deleted:

    • CatBoost
    • LightGBM
    • TensorFlow
    • XGBoost

Image 1.4.x

1.4.35

  • Adapted images to be used in subnets with a user-defined DNS zone.

1.4

  • The following components were updated:

    • HBase to 1.3.5
    • Hadoop to 2.10.0
    • Hive to 2.3.6
    • Flume to 1.9.0
    • Livy to 0.7.0
    • Oozie to 5.2.0
    • Spark to 2.4.6
    • Sqoop to 1.4.7
    • Tez to 0.9.2
    • Zeppelin to 0.8.2
    • ZooKeeper to 3.4.14

  • Python updated to version 3.7.9.

  • The following libraries were updated:

    • CatBoost to 0.20.2
    • IPython to 7.9.0
    • ipykernel to 5.1.3
    • LightGBM to 2.3.0
    • Matplotlib to 3.1.1
    • pandas to 0.25.3
    • PyArrow to 0.13.0
    • PyHive to 0.6.1
    • scikit-learn to 0.21.3
    • TensorFlow to 1.15.0
    • XGBoost to 0.90
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