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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>
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.