Files
impala/testdata/datasets
Peter Rozsa 1d05381b7b IMPALA-11745: Add Hive's ESRI geospatial functions as builtins
This change adds geospatial functions from Hive's ESRI library
as builtin UDFs. Plain Hive UDFs are imported without changes,
but the generic and varargs functions are handled differently;
generic functions are added with all of the combinations of
their parameters (cartesian product of the parameters), and
varargs functions are unfolded as an nth parameter simple
function. The varargs function wrappers are generated at build
time and they can be configured in
gen_geospatial_udf_wrappers.py. These additional steps are
required because of the limitations in Impala's UDF Executor
(lack of varargs support and only partial generics support)
which could be further improved; in this case, the additional
wrapping/mapping steps could be removed.

Changes regarding function handling/creating are sourced from
https://gerrit.cloudera.org/c/19177

A new backend flag was added to turn this feature on/off
as "geospatial_library". The default value is "NONE" which
means no geospatial function gets registered
as builtin, "HIVE_ESRI" value enables this implementation.

The ESRI geospatial implementation for Hive currently only
available in Hive 4, but CDP Hive backported it to Hive 3,
therefore for Apache Hive this feature is disabled
regardless of the "geospatial_library" flag.

Known limitations:
 - ST_MultiLineString, ST_MultiPolygon only works
   with the WKT overload
 - ST_Polygon supports a maximum of 6 pairs of coordinates
 - ST_MultiPoint, ST_LineString supports a maximum of 7
   pairs of coordinates
 - ST_ConvexHull, ST_Union supports a maximum of 6 geoms

These limits can be increased in gen_geospatial_udf_wrappers.py

Tests:
 - test_geospatial_udfs.py added based on
   https://github.com/Esri/spatial-framework-for-hadoop

Co-Authored-by: Csaba Ringhofer <csringhofer@cloudera.com>

Change-Id: If0ca02a70b4ba244778c9db6d14df4423072b225
Reviewed-on: http://gerrit.cloudera.org:8080/19425
Reviewed-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
2023-02-07 20:18:47 +00:00
..

This directory contains Impala test data sets. The directory layout is structured as follows:

datasets/
   <data set>/<data set>_schema_template.sql
   <data set>/<data files SF1>/data files
   <data set>/<data files SF2>/data files

Where SF is the scale factor controlling data size. This allows for scaling the same schema to
different sizes based on the target test environment.

The schema template SQL files have the following format:

  The goal is to provide a single place to define a table + data files
  and have the schema and data load statements generated for each combination of file
  format, compression, etc. The way this works is by specifying how to create a
  'base table'. The base table can be used to generate tables in other file formats
  by performing the defined INSERT / SELECT INTO statement. Each new table using the
  file format/compression combination needs to have a unique name, so all the
  statements are pameterized on table name.
  The template file is read in by the 'generate_schema_statements.py' script to
  to generate all the schema for the Impala benchmark tests.

  Each table is defined as a new section in the file with the following format:

  ====
  ---- SECTION NAME
  section contents
  ...
  ---- ANOTHER SECTION
  ... section contents
  ---- ... more sections...

  Note that tables are delimited by '====' and that even the first table in the
  file must include this header line.

  The supported section names are:

  DATASET
      Data set name - Used to group sets of tables together
  BASE_TABLE_NAME
      The name of the table within the database
  CREATE
      Explicit CREATE statement used to create the table (executed by Impala)
  CREATE_HIVE
      Same as the above, but will be executed by Hive instead. If specified,
      'CREATE' must not be specified.
  CREATE_KUDU
      Customized CREATE TABLE statement used to create the table for Kudu-specific
      syntax.

  COLUMNS
  PARTITION_COLUMNS
  ROW_FORMAT
  HBASE_COLUMN_FAMILIES
  TABLE_PROPERTIES
  HBASE_REGION_SPLITS
      If no explicit CREATE statement is provided, a CREATE statement is generated
      from these sections (see 'build_table_template' function in
      'generate-schema-statements.py' for details)

  ALTER
      A set of ALTER statements to be executed after the table is created
      (typically to add partitions, but may also be used for other settings that
      cannot be specified directly in the CREATE TABLE statement).

      These statements are ignored for HBase and Kudu tables.

  LOAD
      The statement used to load the base (text) form of the table. This is
      typically a LOAD DATA statement.

  DEPENDENT_LOAD
  DEPENDENT_LOAD_KUDU
  DEPENDENT_LOAD_HIVE
  DEPENDENT_LOAD_ACID
      Statements to be executed during the "dependent load" phase. These statements
      are run after the initial (base table) load is complete.

  HIVE_MAJOR_VERSION
       The required major version of Hive for this table. If the major version
       of Hive at runtime does not exactly match the version specified in this section,
       the table will be skipped.

       NOTE: this is not a _minimum_ version -- if HIVE_MAJOR_VERSION specifies '2',
                   the table will _not_ be loaded/created on Hive 3.