After approximately a year of beta releases, Apache Kudu has reached version 1.0. This version number signifies that the development team feels that Kudu is stable enough for usage in production environments.
If you are new to Kudu, check out its list of features and benefits.
Kudu 1.0.0 delivers a number of new features, bug fixes, and optimizations.
Removal of multiversion concurrency control (MVCC) history is now supported. This is known as tablet history GC. This allows Kudu to reclaim disk space, where previously Kudu would keep a full history of all changes made to a given table since the beginning of time. Previously, the only way to reclaim disk space was to drop a table.
Kudu will still keep historical data, and the amount of history retained is
controlled by setting the configuration flag
which defaults to 15 minutes (expressed in seconds). The timestamp
represented by the current time minus
tablet_history_max_age_sec is known
as the ancient history mark (AHM). When a compaction or flush occurs, Kudu
will remove the history of changes made prior to the ancient history mark.
This only affects historical data; currently-visible data will not be
removed. A specialized maintenance manager background task to remove existing
"cold" historical data that is not in a row affected by the normal compaction
process will be added in a future release.
Most of Kudu’s command line tools have been consolidated under a new
kudu tool. This reduces the number of large binaries distributed
with Kudu and also includes much-improved help output.
The Kudu Flume Sink now supports processing events containing Avro-encoded
records, using the new
Administrative tools including
kudu cluster ksck now support running
against multi-master Kudu clusters.
The output of the
ksck tool is now colorized and much easier to read.
The C++ client API now supports writing data in
This can provide higher throughput for ingest workloads.
The performance of comparison predicates on dictionary-encoded columns has been substantially optimized. Users are encouraged to use dictionary encoding on any string or binary columns with low cardinality, especially if these columns will be filtered with predicates.
The Java client is now able to prune partitions from scanners based on the provided predicates. For example, an equality predicate on a hash-partitioned column will now only access those tablets that could possibly contain matching data. This is expected to improve performance for the Spark integration as well as applications using the Java client API.
The performance of compaction selection in the tablet server has been substantially improved. This can increase the efficiency of the background maintenance threads and improve overall throughput of heavy write workloads.
The policy by which the tablet server retains write-ahead log (WAL) files has been improved so that it takes into account other replicas of the tablet. This should help mitigate the spurious eviction of tablet replicas on machines that temporarily lag behind the other replicas.
Kudu 1.0.0 maintains client-server wire-compatibility with previous releases. Applications using the Kudu client libraries may be upgraded either before, at the same time, or after the Kudu servers.
Kudu 1.0.0 does not maintain server-server wire compatibility with previous releases. Therefore, rolling upgrades between earlier versions of Kudu and Kudu 1.0.0 are not supported.
kudu-pbc-dump tool has been removed. The same functionality is now
kudu pbc dump.
kudu-ksck tool has been removed. The same functionality is now
kudu cluster ksck.
cfile-dump tool has been removed. The same functionality is now
kudu fs cfile dump.
log-dump tool has been removed. The same functionality is now
kudu wal dump and
kudu local_replica dump wals.
kudu-admin tool has been removed. The same functionality is now
kudu table and
kudu-fs_dump tool has been removed. The same functionality is now
kudu fs dump.
kudu-ts-cli tool has been removed. The same functionality is now
kudu remote_replica, and
kudu-fs_list tool has been removed and some similar useful
functionality has been moved under 'kudu local_replica'.
Some configuration flags are now marked as 'unsafe' and 'experimental'. Such flags
are disallowed by default. Users may access these flags by enabling the additional
--unlock_experimental_flags. Usage of such flags
is not recommended, as the flags may be removed or modified with no deprecation period
and without notice in future Kudu releases.
TIMESTAMP column type has been renamed to
UNIXTIME_MICROS in order to
reduce confusion between Kudu’s timestamp support and the timestamps supported
by other systems such as Apache Hive and Apache Impala (incubating). Existing
tables will automatically be updated to use the new name for the type.
Clients upgrading to the new client libraries must move to the new name for the type. Clients using old client libraries will continue to operate using the old type name, even when connected to clusters that have been upgraded. Similarly, if clients are upgraded before servers, existing timestamp columns will be available using the new type name.
KuduSession methods in the C++ library are no longer advertised as thread-safe
to have one set of semantics for both C++ and Java Kudu client libraries.
KuduScanToken::TabletServers method in the C++ library has been removed.
The same information can now be found in the KuduScanToken::tablet method.
KuduEventProducer interface used to process Flume events into Kudu operations
for the Kudu Flume Sink has changed, and has been renamed
The existing `KuduEventProducer`s have been updated for the new interface, and have
been renamed similarly.
Kudu is primarily designed for analytic use cases. You are likely to encounter issues if a single row contains multiple kilobytes of data.
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.
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.
Tables must be manually pre-split into tablets using simple or compound primary keys. Automatic splitting is not yet possible. Range partitions may be added or dropped after a table has been created. See Schema Design for more information.
Data in existing tables cannot currently be automatically repartitioned. As a workaround, create a new table with the new partitioning and insert the contents of the old table.
Kudu does not currently include any built-in features for backup and restore. Users are encouraged to use tools such as Spark or Impala to export or import tables as necessary.
To use Kudu with Impala, you must install a special release of Impala called Impala_Kudu. Obtaining and installing a compatible Impala release is detailed in Kudu’s 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 of the way through, its partial effects will not be rolled back.
All queries will be distributed across all Impala hosts 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.
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 use large tables.
Impala is only able to push down predicates involving
BETWEEN comparisons between any column and a literal value, and
for integer columns only. For example, for a table with an integer key
a string key
name, the predicate
WHERE ts >= 12345 will convert into an
efficient range scan, whereas
where name > 'lipcon' will currently fetch all
data from the table and evaluate the predicate within Impala.
Authentication and authorization features are not implemented.
Data encryption is not built in. Kudu has been reported to run correctly
on systems using local block device encryption (e.g.
ALTER TABLE is not yet fully supported via the client APIs. More
operations will become available in future releases.
The following are known bugs and issues with the current release of Kudu. They will be addressed in later releases. Note that this list is not exhaustive, and is meant to communicate only the most important known issues.
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.
Due to a known bug in Linux kernels prior to 3.8, running Kudu on
ext4 mount points
may cause a subsequent
fsck to fail with errors such as
Logical start <N> does
not match logical start <M> at next level. These errors are repairable using
but may impact server restart time.
This affects RHEL/CentOS 6.8 and below. A fix is planned for RHEL/CentOS 6.9. RHEL 7.0 and higher are not affected. Ubuntu 14.04 and later are not affected. SLES 12 and later are not affected.