Files
sql-server-samples/samples/features/sql-big-data-cluster/data-virtualization/storage-pool/web-clickstreams-hdfs-parquet.sql
T

111 lines
4.5 KiB
Transact-SQL

USE sales
GO
-- Create external data source for HDFS inside SQL big data cluster.
--
IF NOT EXISTS(SELECT * FROM sys.external_data_sources WHERE name = 'SqlStoragePool')
IF SERVERPROPERTY('ProductLevel') = 'CTP2.5'
CREATE EXTERNAL DATA SOURCE SqlStoragePool
WITH (LOCATION = 'sqlhdfs://nmnode-0-0.nmnode-0-svc:50070');
ELSE IF SERVERPROPERTY('ProductLevel') = 'CTP3.0'
CREATE EXTERNAL DATA SOURCE SqlStoragePool
WITH (LOCATION = 'sqlhdfs://controller-svc:8080/default');
-- Create file format for parquet file with appropriate properties.
--
IF NOT EXISTS(SELECT * FROM sys.external_file_formats WHERE name = 'parquet_file')
CREATE EXTERNAL FILE FORMAT parquet_file
WITH (
FORMAT_TYPE = PARQUET
);
-- Create external table over HDFS data source (SqlStoragePool) in
-- SQL Server 2019 big data cluster. The SqlStoragePool data source
-- is a special data source that is available in any new database in
-- SQL Master instance.
--
IF NOT EXISTS(SELECT * FROM sys.external_tables WHERE name = 'web_clickstreams_hdfs_parquet')
CREATE EXTERNAL TABLE [web_clickstreams_hdfs_parquet]
("wcs_click_date_sk" BIGINT , "wcs_click_time_sk" BIGINT , "wcs_sales_sk" BIGINT , "wcs_item_sk" BIGINT , "wcs_web_page_sk" BIGINT , "wcs_user_sk" BIGINT)
WITH
(
DATA_SOURCE = SqlStoragePool,
LOCATION = '/user/hive/warehouse/web_clickstreams',
FILE_FORMAT = parquet_file
);
GO
-- Join external table with local tables
--
SELECT
wcs_user_sk,
SUM( CASE WHEN i_category = 'Books' THEN 1 ELSE 0 END) AS book_category_clicks,
SUM( CASE WHEN i_category_id = 1 THEN 1 ELSE 0 END) AS [Home & Kitchen],
SUM( CASE WHEN i_category_id = 2 THEN 1 ELSE 0 END) AS [Music],
SUM( CASE WHEN i_category_id = 3 THEN 1 ELSE 0 END) AS [Books],
SUM( CASE WHEN i_category_id = 4 THEN 1 ELSE 0 END) AS [Clothing & Accessories],
SUM( CASE WHEN i_category_id = 5 THEN 1 ELSE 0 END) AS [Electronics],
SUM( CASE WHEN i_category_id = 6 THEN 1 ELSE 0 END) AS [Tools & Home Improvement],
SUM( CASE WHEN i_category_id = 7 THEN 1 ELSE 0 END) AS [Toys & Games],
SUM( CASE WHEN i_category_id = 8 THEN 1 ELSE 0 END) AS [Movies & TV],
SUM( CASE WHEN i_category_id = 9 THEN 1 ELSE 0 END) AS [Sports & Outdoors]
FROM [dbo].[web_clickstreams_hdfs_parquet]
INNER JOIN item it ON (wcs_item_sk = i_item_sk
AND wcs_user_sk IS NOT NULL)
GROUP BY wcs_user_sk;
GO
-- Create view used for ML services training stored procedure
CREATE OR ALTER VIEW [dbo].[web_clickstreams_hdfs_book_clicks]
AS
SELECT
/* There is bug in TPCx-BB data generator which results in data where all users have purchased books.
This will not work for the ML training purposes. So we will treat users with 1-5 clicks in the book category as
not interested in books. */
CASE WHEN q.clicks_in_category < 6 THEN 0 ELSE q.clicks_in_category END AS clicks_in_category,
CASE WHEN cd.cd_education_status IN ('Advanced Degree', 'College', '4 yr Degree', '2 yr Degree') THEN 1 ELSE 0 END AS college_education,
CASE WHEN cd.cd_gender = 'M' THEN 1 ELSE 0 END AS male,
COALESCE(cd.cd_credit_rating, 'Unknown') as cd_credit_rating,
q.clicks_in_1,
q.clicks_in_2,
q.clicks_in_3,
q.clicks_in_4,
q.clicks_in_5,
q.clicks_in_6,
q.clicks_in_7,
q.clicks_in_8,
q.clicks_in_9,
q.wcs_user_sk
FROM(
SELECT
w.wcs_user_sk,
SUM( CASE WHEN i.i_category = 'Books' THEN 1 ELSE 0 END) AS clicks_in_category,
SUM( CASE WHEN i.i_category_id = 1 THEN 1 ELSE 0 END) AS clicks_in_1,
SUM( CASE WHEN i.i_category_id = 2 THEN 1 ELSE 0 END) AS clicks_in_2,
SUM( CASE WHEN i.i_category_id = 3 THEN 1 ELSE 0 END) AS clicks_in_3,
SUM( CASE WHEN i.i_category_id = 4 THEN 1 ELSE 0 END) AS clicks_in_4,
SUM( CASE WHEN i.i_category_id = 5 THEN 1 ELSE 0 END) AS clicks_in_5,
SUM( CASE WHEN i.i_category_id = 6 THEN 1 ELSE 0 END) AS clicks_in_6,
SUM( CASE WHEN i.i_category_id = 7 THEN 1 ELSE 0 END) AS clicks_in_7,
SUM( CASE WHEN i.i_category_id = 8 THEN 1 ELSE 0 END) AS clicks_in_8,
SUM( CASE WHEN i.i_category_id = 9 THEN 1 ELSE 0 END) AS clicks_in_9
FROM web_clickstreams_hdfs_parquet as w
INNER JOIN item as i ON (w.wcs_item_sk = i_item_sk
AND w.wcs_user_sk IS NOT NULL)
GROUP BY w.wcs_user_sk
) AS q
INNER JOIN customer as c ON q.wcs_user_sk = c.c_customer_sk
INNER JOIN customer_demographics as cd ON c.c_current_cdemo_sk = cd.cd_demo_sk;
GO
-- Inspect top 100 rows
SELECT TOP(100) * FROM web_clickstreams_hdfs_book_clicks;
GO
-- Cleanup
/*
DROP EXTERNAL TABLE [dbo].[web_clickstreams_hdfs_parquet];
GO
*/