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Henry Robinson
Henry Robinson IMPALA-1122: Compute stats with partition granularity
This patch adds the ability to compute and drop column and table
statistics at partition granularity.

The following commands are added. Detail about the implementation

COMPUTE INCREMENTAL STATS <tbl_name> [PARTITION <partition_spec>]

This variant of COMPUTE STATS will, ultimately, do the same thing as the
traditional COMPUTE STATS statement, but does so by caching the
intermediate state of the computation for each partition in the Hive
MetaStore. If the PARTITION clause is added, the computation is
performed for only that partition. If the PARTITION clause is omitted,
incremental stats are updated only for those partitions with missing
incremental stats (e.g. one column does not have stats, or incremental
stats was never computed for this partition). In this patch, incremental
stats are only invalidated when a DROP STATS variant is executed. Future
patches can automatically invalidate the statistics after REFRESH or
INSERT queries, etc.


This variant of DROP stats removes the incremental statistics for the
given table. It does *not* recalculate the statistics for the whole
table, so this should be used only to invalidate the intermediate state
for a partition which will shortly be subject to COMPUTE INCREMENTAL
STATS. The point of this variant is to allow users to notify Impala when
they believe a partition has changed significantly enough to warrant
recomputation of its statistics. It is not necessary for new partitions;
Impala will detect that they do not have any valid statistics.


This is achieved by adapting the existing HLL UDA via swapping its
finalize method for a new one which returns the intermediate HLL
buckets, rather than aggregating and then disposing of them. This
intermediate state is then returned to Impala's,
which then passes the intermediate state back to the frontend to be
ultimately stored in the HMS.

This intermediate state is computed on a per-partition basis by grouping
the input to the UDA by partition. Thus, the incremental computation
produces one row for each partition selected (the set of which might be
quite small, if there are few partitions without valid incremental
stats: this is the point of the new commands).

At the same time, the query coordinator aggregates the output of the UDA
to produce table-level statistics. This computation incorporates any
existing (and not re-computed) intermediate partition state which is
passed to the coordinator by the frontend. The resulting statistics are
saved to the table as normal.

Intermediate statistics are serialised to the HMS by writing a Thrift
structure's serialised form to the partition's 'parameters' map. There
is a schema-imposed limit of 4000 characters to the serialised string,
which is exacerbated by the fact that the Thrift representation must
first be base-64 encoded to avoid type errors in the HMS. The current
patch breaks the encoded structure into 4k chunks, and then recombines
them on read. The alltypes table (11 columns) takes about three of these
chunks. This may mean that incremental stats are not suitable for
particularly wide tables: these structures could be zipped before
encoding for some space savings. In the meantime, the NDV estimates are
run-length encoded (since they are generally sparse); this can result in
substantial space savings.

Change-Id: If82cf4753d19eb532265acb556f798b95fbb0f34
Tested-by: jenkins
Reviewed-by: Henry Robinson <>
Latest commit bf72b57 Sep 16, 2014
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README UDF/UDA interface, some examples and developer libs. Jan 8, 2014 Add symbol resolution during analysis for create function stmts. Jan 8, 2014 Add decimal UDF/UDA support. May 30, 2014
uda-sample.h Add symbol resolution during analysis for create function stmts. Jan 8, 2014


This folder is a sample for how to develop UDFs and UDAs for Impala.

All of the files here are part of the UDF developer kit.

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