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[[release_notes]]
= Kudu Release Notes

:author: Kudu Team
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== Introducing Kudu

Kudu is a columnar storage manager developed for the Hadoop platform. Kudu shares
the common technical properties of Hadoop ecosystem applications: it runs on
commodity hardware, is horizontally scalable, and supports highly available operation.

Kudu’s design sets it apart. Some of Kudu’s benefits include:

* Fast processing of OLAP workloads.
* Integration with MapReduce, Spark and other Hadoop ecosystem components.
* Tight integration with Cloudera Impala, making it a good, mutable alternative to
using HDFS with Parquet. See link:kudu_impala_integration.html[Kudu Impala Integration].
* Strong but flexible consistency model.
* Strong performance for running sequential and random workloads simultaneously.
* Easy to administer and manage with Cloudera Manager.
* Efficient utilization of hardware resources.
* High availability. Tablet Servers and Masters use the Raft Consensus Algorithm.
Given a replication factor of `2f+1`, if `f` tablet servers serving a given tablet
fail, the tablet is still available.
+
NOTE: High availability for masters is not supported during the public beta.

By combining all of these properties, Kudu targets support for families of
applications that are difficult or impossible to implement on current generation
Hadoop storage technologies.

=== Kudu-Impala Integration Features
`CREATE TABLE`::
  Impala supports creating and dropping tables using Kudu as the persistence layer.
  The tables follow the same internal / external approach as other tables in Impala,
  allowing for flexible data ingestion and querying.
`INSERT`::
  Data can be inserted into Kudu tables from Impala using the same mechanisms as
  any other table with HDFS or HBase persistence.
`UPDATE` / `DELETE`::
  Impala supports the `UPDATE` and `DELETE` SQL commands to modify existing data in
  a Kudu table row-by-row or as a batch. The syntax of the SQL commands is chosen
  to be as compatible as possible to existing solutions. In addition to simple `DELETE`
  or `UPDATE` commands, you can specify complex joins in the `FROM` clause of the query
  using the same syntax as a regular `SELECT` statement.
Flexible Partitioning::
  Similar to partitioning of tables in Hive, Kudu allows you to dynamically
  pre-split tables by hash or range into a predefined number of tablets, in order
  to distribute writes and queries evenly across your cluster. You can partition by
  any number of primary key columns, by any number of hashes and an optional list of
  split rows.
Parallel Scan::
  To achieve the highest possible performance on modern hardware, the Kudu client
  within Impala parallelizes scans to multiple tablets.
High-efficiency queries::
  Where possible, Impala pushes down predicate evaluation to Kudu, so that predicates
  are evaluated as close as possible to the data. Query performance is comparable
  to Parquet in many workloads.

== About the Kudu Public Beta

This release of Kudu is a public beta. Do not run this beta release on production clusters. During the
public beta period, Kudu will be supported via a link:https://issues.cloudera.org/projects/KUDU
[public JIRA] and a public mailing list link:mailto:kudu-user@cloudera.org[mailing
list], which will be monitored by the Kudu development team and community members.
Commercial support is not available at this time.

* You can submit any issues or feedback related to your Kudu experience via either
the JIRA system or the mailing list. The Kudu development team and community members
will respond and assist as quickly as possible.
* The Kudu team will work with early adopters to fix bugs and release new binary drops
when fixes or features are ready. However, we cannot commit to issue resolution or
bug fix delivery times during the public beta period, and it is possible that some
fixes or enhancements will not be selected for a release.
* We can't guarantee timeframes or contents for future beta code drops. However,
they will be announced to the user group when they occur.
* No guarantees are made regarding upgrades from this release to follow-on releases.
While multiple drops of beta code are planned, we can't guarantee their schedules
or contents.

== Resources

- link:http://getkudu.io[Kudu Website]
- link:http://github.com/cloudera/kudu[Kudu Github Repository]
- link:index.html.html[Kudu Documentation]

== Installation Options
* A Quickstart VM is provided to get you up and running quickly.
* You can install parcels or packages in clusters managed by Cloudera Manager, or
packages in standalone CDH clusters.
* You can build Kudu from source.

For full installation details, see link:installation.html[Kudu Installation].

== Limitations of the Public Beta

=== Operating System Limitations
* RHEL 6.4 or newer, CentOS 6.4 or newer, and Ubuntu Trusty are are the only
operating systems supported for installation in the public beta.
Others may work but have not been tested.

=== Storage Limitations
* Kudu has been tested with up to 4 TB of data per tablet server. More testing
is needed for denser storage configurations.

=== Schema Limitations
* Testing with more than 20 columns has been limited.
* Multi-kilobyte rows have not been thoroughly tested.
* The columns which make up the primary key must be listed first in the schema.
* Key columns cannot be altered. You must drop and recreate a table to change its keys.
* Key columns must not be null.
* Columns with `DOUBLE`, `FLOAT`, or `BOOL` types are not allowed as part of a
primary key definition.
* Type and nullability of existing columns cannot be changed by altering the table.
* A table’s primary key cannot be changed.
* Dropping a column does not immediately reclaim space. Compaction must run first.
There is no way to run compaction manually, but dropping the table will reclaim the
space immediately.

=== Ingest Limitations
* Ingest via Sqoop or Flume is not supported in the public beta. The recommended
approach for bulk ingest is to use Impala’s `CREATE TABLE AS SELECT` functionality
or use the Kudu's Java or C++ API.
* Tables must be manually pre-split into tablets using simple or compound primary
keys. Automatic splitting is not yet possible. Instead, add split rows at table creation.
* Tablets cannot currently be merged. Instead, create a new table with the contents
of the old tables to be merged.

=== Cloudera Manager Limitations
* Some metrics, such as latency histograms, are not yet available in Cloudera Manager.
* Some service and role chart pages are still under development. More charts and
metrics will be visible in future releases.

=== Replication and Backup Limitations
* Replication and failover of Kudu masters is considered experimental. It is
recommended to run a single master and periodically perform a manual backup of its data directories.

=== Impala Limitations
* To use Kudu with Impala, you must install a special release of Impala. Obtaining
and installing a compatible Impala release is detailed in Kudu's
link:kudu_impala_integration.html[Impala Integration] documentation.
* To use Impala_Kudu alongside an existing Impala instance, you must install using parcels.
* Updates, inserts, and deletes via Impala are non-transactional. If a query
fails part-way, its partial effects will not be rolled back..
* All queries will be distributed across all Impala nodes which host a replica
of the target table(s), even if a predicate on a primary key could correctly
restrict the query to a single tablet. This limits the maximum concurrency of
short queries made via Impala.
* ALTER TABLE on Kudu tables is not yet supported via Impala.
* No timestamp and decimal type support.
* The maximum parallelism of a single query is limited to the number of tablets
in a table. For good analytic performance, aim for 10 or more tablets per host
or large tables.
* Impala is only able to push down predicates involving `=`, `<=`, `>=`,
or `BETWEEN` comparisons between a column and a literal value. Impala pushes down
predicates`<` and `>` for integer columns only. For example, for a table with
an integer key `ts`, and a float key `income`, the predicate `WHERE ts >= 12345`
will convert into an efficient range scan, whereas ‘where income > 1000000.0’
will currently fetch all data from the table and evaluate the predicate within Impala.

=== Security Limitations
* Authentication and authorization are not included in the public beta.
* Data encryption is not included in the public beta.

=== Client and API Limitations
* Potentially-incompatible C++ and Java API changes may be required during the
public beta.
* ALTER TABLE is not yet fully supported via the client APIs. More ALTER TABLE
operations will become available in future betas.
* The Python API is not supported.

=== Application Integration Limitations
* The Spark DataFrame implementation is not yet complete.

=== Other Known Issues
The following are known bugs and issues with the current beta release. They will
be addressed in later beta releases.

* Building Kudu from source using `gcc` 4.6 causes runtime and test failures. Be sure
you are using a different version of `gcc` if you build Kudu from source.
* If the Kudu master is configured with the `-log_fsync_all` option, tablet servers
and clients will experience frequent timeouts, and the cluster may become unusable.
* If a tablet server has a very large number of tablets, it may take several minutes
to start up. It is recommended to limit the number of tablets per server to 100 or fewer.
Consider this limitation when pre-splitting your tables. If you notice slow start-up times,
you can monitor the number of tablets per server in the web UI.

== Next Steps
- link:quickstart.html[Kudu Quickstart]
- link:installation.html[Installing Kudu]
- link:configuration.html[Configuring Kudu]