The Apache Kudu team is happy to announce the release of Kudu 1.17.0! Kudu is an open source storage engine for structured data which supports low-latency random access together with efficient analytical access patterns. It is designed within the context of the Apache Hadoop ecosystem and supports many integrations with other data analytics projects both inside and outside of the Apache Software Foundation.
The new release adds several new features and improvements, including the following: - Kudu now supports encrypting data at rest. Kudu supports AES-128-CTR, AES-192-CTR, and AES-256-CTR ciphers to encrypt data, supports Apache Ranger KMS and Apache Hadoop KMS. See Data at rest for more details. - Kudu now supports range-specific hash schemas for tables. It’s now possible to add ranges with their own unique hash schema independent of the table-wide hash schema. This can be done at table creation time and while altering the table. It’s controlled by the --enable_per_range_hash_schemas master flag which is enabled by default (see KUDU-2671). - Kudu now supports soft-deleted tables. Kudu keeps a soft-deleted table aside for a period of time (a.k.a. reservation), not purging the data yet. The table can be restored/recalled back before its reservation expires. The reservation period can be customized via Kudu client API upon soft-deleting the table. The default reservation period is controlled by the --default_deleted_table_reserve_seconds master’s flag. NOTE: As of Kudu 1.17 release, the soft-delete functionality is not supported when HMS integration is enabled, but this should be addressed in a future release (see KUDU-3326). - Introduced Auto-Incrementing column. An auto-incrementing column is populated on the server side with a monotonically increasing counter. The counter is local to every tablet, i.e. each tablet has a separate auto incrementing counter (see KUDU-1945). - Kudu now supports experimental non-unique primary key. When a table with non-unique primary key is created, an Auto-Incrementing column named auto_incrementing_id is added automatically to the table as the key column. The non-unique key columns and the Auto-Incrementing column together form the effective primary key (see KUDU-1945). - Introduced Immutable column. It’s useful to represent a semantically constant entity (see KUDU-3353). - An experimental feature is added to Kudu that allows it to automatically rebalance tablet leader replicas among tablet servers. The background task can be enabled by setting the --auto_leader_rebalancing_enabled flag on the Kudu masters. By default, the flag is set to ‘false’ (see KUDU-3390). - Introduced an experimental feature: authentication of Kudu client applications to Kudu servers using JSON Web Tokens (JWT). The JWT-based authentication can be used as an alternative to Kerberos authentication for Kudu applications running at edge nodes where configuring Kerberos might be cumbersome. Similar to Kerberos credentials, a JWT is considered a primary client’s credentials. The server-side capability of JWT-based authentication is controlled by the --enable_jwt_token_auth flag (set ‘false’ by default). When the flat set to ‘true’, a Kudu server is capable of authenticating Kudu clients using the JWT provided by the client during RPC connection negotiation. From its side, a Kudu client authenticates a Kudu server by verifying its TLS certificate. For the latter to succeed, the client should use Kudu client API to add the cluster’s IPKI CA certificate into the list of trusted certificates. - The C++ client scan token builder can now create multiple tokens per tablet. So, it’s now possible to dynamically scale the set of readers/scanners fetching data from a Kudu table in parallel. To use this functionality, use the newly introduced SetSplitSizeBytes() method of the Kudu client API to specify how many bytes of data each token should scan (see KUDU-3393). - Kudu’s default replica placement algorithm is now range and table aware to prevent hotspotting unlike the old power of two choices algorithm. New replicas from the same range are spread evenly across available tablet servers, the table the range belongs to is used as a tiebreaker (see KUDU-3476). - Reduce the memory consumption if there are frequent alter schema operations for tablet servers (see KUDU-3197). - Reduce the memory consumption by implementing memory budgeting for performing RowSet merge compactions (i.e. CompactRowSetsOp maintenance operations). Several flags have been introduced, while the --rowset_compaction_memory_estimate_enabled flag indicates whether to check for available memory necessary to run CompactRowSetsOp maintenance operations (see KUDU-3406). - The above is just a list of the highlights, for a more complete list of new features, improvements and fixes please refer to the release notes: https://kudu.apache.org/releases/1.17.0/docs/release_notes.html. The Apache Kudu project only publishes source code releases. To build Kudu 1.17.0, follow these steps: - Download the Kudu 1.17.0 source release: https://kudu.apache.org/releases/1.17.0/ - Follow the instructions in the documentation to build Kudu 1.17.0 from source: https://kudu.apache.org/releases/1.17.0/docs/installation.html#build_from_source For your convenience, binary JAR files for the Kudu Java client library, Spark DataSource, and other Java integrations are published to the ASF Maven repository and are now available: https://central.sonatype.com/search?q=g:org.apache.kudu%20%20v:1.17.0 The Python client source is also available on PyPI: https://pypi.org/project/kudu-python/ Additionally, experimental Docker images are published to Docker Hub: https://hub.docker.com/r/apache/kudu Regards, The Apache Kudu Team
