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This commit adds a scan node for querying Iceberg metadata tables. The
scan node creates a Java scanner object that creates and scans the
metadata table. The scanner uses the Iceberg API to scan the table after
that the scan node fetches the rows one by one and materialises them
into RowBatches. The Iceberg row reader on the backend does the
translation between Iceberg and Impala types.
There is only one fragment created to query the Iceberg metadata table
which is supposed to be executed on the coordinator node that already
has the Iceberg table loaded. This way there is no need for further
table loading on the executor side.
This change will not cover nested column types, these slots are set to
NULL, it will be done in IMPALA-12205.
Testing:
- Added e2e tests for querying metadata tables
- Updated planner tests
Performance testing:
Created a table and inserted ~5500 rows one by one, this generated
~270000 ALL_MANIFESTS metadata table records. This table is quite wide
and has a String column as well.
I only mention count(*) test on ALL_MANIFESTS, because every row is
materialized in every scenario currently:
- Cold cache: 15.76s
- IcebergApiScanTime: 124.407ms
- MaterializeTupleTime: 8s368ms
- Warm cache: 7.56s
- IcebergApiScanTime: 3.646ms
- MaterializeTupleTime: 7s477ms
Change-Id: I0e943cecd77f5ef7af7cd07e2b596f2c5b4331e7
Reviewed-on: http://gerrit.cloudera.org:8080/20010
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.