パス フィルタリングでのビューの使用 - Advanced SQL Engine - Teradata Database

REPLACE VIEW riverflowview_parquet AS (
SELECT CAST($path.$siteno AS CHAR(10)) TheSite,
CAST($path.$year AS CHAR(4)) TheYear,
CAST($path.$month AS CHAR(2)) TheMonth,
CAST(SUBSTR($path.$day, 1, 2) AS CHAR(2)) TheDay,
Flow,
GageHeight GageHeight1,
Precipitation,
GageHeight2
FROM riverflow_parquet_path
WHERE TheSite = site_no);

SELECT TOP 2 * FROM riverflowview_parquet;

結果:

TheSite  TheYear TheMonth TheDay Site_no    Flow  GageHeight1 Precipitation GageHeight2
-------- ------- -------- ------ --------  ------ ----------- ------------- -----------
09396100    2018     07    15    9396100   153.00         1.96         0.00        1.96
09396100    2018     07    15    9396100   150.00         1.95         0.00        1.95

SELECT thesite,COUNT(*)
FROM riverflowview_parquet WHERE thesite='09396100'
GROUP BY 1;

結果:

TheSite        Count(*)
----------  -----------
09396100           2906

EXPLAIN
SELECT thesite,COUNT(*)
FROM riverflowview_parquet WHERE thesite='09396100'
GROUP BY 1;

結果:

Explanation
---------------------------------------------------------------------------
[...]
  3) We do a single-AMP RETRIEVE step from
     NOS_USR.riverflow_parquet_path in view riverflowview_parquet
     metadata by way of an all-rows scan with a condition of ( "(TD_SYSFNLIB.NosExtractVarFromPath ( NOS_USR.riverflow_parquet_path in view riverflowview_parquet.Location, '/S3/td-usgs.s3.amazonaws.com/', 2 )(CHAR(10), CHARACTER SET UNICODE, NOT CASESPECIFIC))= '09396100 '")
     into Spool 3 (all_amps), which is built locally on that AMP.  Then
     we do a SORT to order Spool 3 by the sort key as the field_id
     list( 3, 2).  The size of Spool 3 is estimated with no confidence
     to be 17 rows (11,985 bytes).  The estimated time for this step is
     0.60 seconds.
  4) We do an all-AMPs RETRIEVE step in TD_Map1 from Spool 3 (Last Use)
     by way of an all-rows scan into Spool 2 (all_amps), which is
     binpacked and redistributed by size to all AMPs in TD_Map1.  The
     size of Spool 2 is estimated with no confidence to be 17 rows (
     12,121 bytes).  The estimated time for this step is 0.16 seconds.
  5) We do an all-AMPs SUM step in TD_MAP1 to aggregate from 3 column
     partitions of NOS_USR.riverflow_parquet_path in view
     riverflowview_parquet by way of external metadata in Spool 2 (Last
     Use) with a condition of ("(TD_SYSFNLIB.NosExtractVarFromPath ( NOS_USR.riverflow_parquet_path in view riverflowview_parquet.Location, '/S3/td-usgs.s3.amazonaws.com/', 2 )(CHAR(10), CHARACTER SET UNICODE, NOT CASESPECIFIC)(FLOAT, FORMAT '-9.99999999999999E-999'))= (NOS_USR.riverflow_parquet_path in view riverflowview_parquet.site_no)"), and the grouping identifier
     in field 1.  Aggregate Intermediate Results are computed globally,
     then placed in Spool 5 in TD_Map1.  The size of Spool 5 is
     estimated with no confidence to be 1,215 rows (1,703,430 bytes).
     The estimated time for this step is 0.77 seconds.
[...]

(3)ではパス フィルタリングを行なっています。メタデータ スプールを構築するためのパス フィルタリング式として定数09396100を使用しています。メタデータ スプールは、クエリーが実際に処理するオブジェクトのリストを識別するスプール テーブルです。

(5)では従来の行フィルタリングを行なっています。場所の文字列から抽出されたサイト番号とParquetデータの値(オブジェクト ストア内の実際のデータ)を比較します。