@gianm gianm released this Dec 1, 2016 · 189 commits to master since this release

Druid 0.9.2 contains hundreds of performance improvements, stability improvements, and bug fixes from over 30 contributors. Major new features include a new groupBy engine, ability to disable rollup at ingestion time, ability to filter on longs, new encoding options for long-typed columns, performance improvements for HyperUnique and DataSketches, a query cache implementation based on Caffeine, a new lookup extension exposing fine grained caching strategies, support for reading ORC files, and new aggregators for variance and standard deviation.

The full list of changes is here: https://github.com/druid-io/druid/pulls?utf8=%E2%9C%93&q=is%3Apr%20is%3Aclosed%20milestone%3A0.9.2

Documentation for this release is here: http://druid.io/docs/0.9.2/


New groupBy engine

Druid now includes a new groupBy engine, rewritten from the ground up for better performance and memory management. Benchmarks show a 2–5x performance boost on our test datasets. The new engine also supports strict limits on memory usage and the option to spill to disk when memory is exhausted, avoiding result row count limitations and potential OOMEs generated by the previous engine.

The new engine is off by default, but you can enable it through configuration or query context parameters. We intend to enable it by default in a future version of Druid.

See "implementation details" on http://druid.io/docs/0.9.2/querying/groupbyquery.html#implementation-details for documentation and configuration.

Added in #2998 by @gianm.

Ability to disable rollup

Since its inception, Druid has had a concept of "dimensions" and "metrics" that applied both at ingestion time and at query time. Druid is unique in that it is one of the only databases that supports aggregation at data loading time, which we call "rollup". But, for some use cases, ingestion-time rollup is not desired, and it's better to load the original data as-is. With rollup disabled, one row in Druid will be created for each input row.

Query-time aggregation is, of course, still supported through the groupBy, topN, and timeseries queries.

See the "rollup" flag on http://druid.io/docs/0.9.2/ingestion/index.html for documentation. By default, rollup remains enabled.

Added in #3020 by @kaijianding.

Ability to filter on longs

Druid now supports sophisticated filtering on integer-typed columns, including long metrics and the special __time column. This opens up a number of new capabilities:

Druid does not yet support grouping on longs. We intend to add this capability in a future release.

Added in #3180 by @jon-wei.

New long encodings

Until now, all integer-typed columns in Druid, including long metrics and the special __time column, were stored as 64-bit longs optionally compressed in blocks with LZ4. Druid 0.9.2 adds new encoding options which, in many cases, can reduce file sizes and improve performance:

  • Long encoding option "auto", which potentially uses table or delta encoding to use fewer than 64 bits per row. The "longs" encoding option is the default behavior, which always uses 64 bits.
  • Compression option "none", which is like the old "uncompressed" option, except it offers a speedup by bypassing block copying.

The default remains "longs" encoding + "lz4" compression. In our testing, two options that often yield useful benefits are "auto" + "lz4" (generally smaller than longs + lz4) and "auto" + "none" (generally faster than longs + lz4, file size impact varies). See the PR for full test results.

See "metricCompression" and "longEncoding" on http://druid.io/docs/0.9.2/ingestion/batch-ingestion.html for documentation.

Added in #3148 by @acslk.

Sketch performance improvements

  • DataSketches speedups of up to 80% from #3471.
  • HyperUnique speedups of 19–30% from #3314, used for "hyperUnique" and "cardinality" aggregators.

New extensions

And much more!

The full list of changes is here: https://github.com/druid-io/druid/pulls?utf8=%E2%9C%93&q=is%3Apr%20is%3Aclosed%20milestone%3A0.9.2

Updating from

Rolling updates

The standard Druid update process described by http://druid.io/docs/0.9.2/operations/rolling-updates.html should be followed for rolling updates.

Query time lookups

The druid-namespace-lookup extension, which was deprecated in 0.9.1 in favor of druid-lookups-cached-global, has been removed in 0.9.2. If you are using druid-namespace-lookup, migrate to druid-lookups-cached-global before upgrading to 0.9.2. See our migration guide for details: http://druid.io/docs/

Other notes

Please note the following changes:

  • Druid now ships Guice 4.1.0 rather than 4.0-beta (#3222). This conflicts with the version shipped in some Hadoop distributions, so for Hadoop indexing you may need to adjust your mapreduce.job.classloader or mapreduce.job.user.classpath.first options. In testing we have found this to be an effective workaround. See http://druid.io/docs/0.9.2/operations/other-hadoop.html for details.
  • If you are using Roaring bitmaps, note that compressRunOnSerialization now defaults to true. As a result, segments written will not be readable by Druid 0.8.1 or earlier. If you need segments written by Druid 0.9.2 to be readable by 0.8.1, and you are using Roaring bitmaps, you must set compressRunOnSerialization = false. By default, bitmaps are Concise, not Roaring, so this point will not apply to you unless you overrode that. See #3228 for details.
  • If you use the new long encoding or compression options, segments written by Druid will not be readable by any version older than 0.9.2. If you don't use the new options, segments will remain backwards compatible.
  • If you are using the experimental Kafka indexing service, there is a known issue that may cause task supervision to hang when it tries to stop all running tasks simultaneously during the upgrade process. To prevent this from happening, you can shutdown all supervisors and wait for the indexing tasks to complete before updating your overlord. Alternatively, you can set chatThreads in the supervisor tuning configuration to a value greater than the number of running tasks as a workaround.


Thanks to everyone who contributed to this release!