tasks/offline-compute/PySpark/pyspark_012/init/init_db.py

#!/usr/bin/env python3
"""pyspark_012 database initialization: create tables + load seed data"""
from pyspark.sql import SparkSession

spark = SparkSession.builder \
    .appName('dataclaw_eval_init_pyspark_012') \
    .enableHiveSupport() \
    .config('spark.sql.warehouse.dir', '/tmp/hive_warehouse') \
    .getOrCreate()

spark.sql('CREATE DATABASE IF NOT EXISTS internal_platform_db')

# Create input table 1: priority info
spark.sql('''
CREATE TABLE IF NOT EXISTS internal_platform_db.sec_app_hy_top_500_sites_tag_v1_pyspark_100 (
    `host` STRING,
    `fld` STRING,
    `priority` STRING,
    `is_host` STRING
)
STORED AS ORC
''')

spark.sql('''
INSERT INTO TABLE internal_platform_db.sec_app_hy_top_500_sites_tag_v1_pyspark_100
VALUES
    ('www.example.com', 'example.com', 'P1', '1'),
    ('news.test.org', 'test.org', 'P2', '0'),
    ('blog.demo.net', 'demo.net', 'P3', '1')
''')

# Create input table 2: daily parse results
spark.sql('''
CREATE TABLE IF NOT EXISTS internal_platform_db.ai_engine_classify_parse_result_daily_pyspark_100 (
    `cos_path` STRING,
    `url` STRING,
    `cos_url` STRING,
    `language` STRING,
    `web_type` STRING,
    `ori_title` STRING,
    `content` STRING,
    `publish_time` STRING,
    `site_name` STRING,
    `ana_title` STRING,
    `cont_title` STRING,
    `author_src` STRING,
    `html_md` STRING,
    `if_contain_dirty_char` STRING,
    `tag` STRING,
    `host` STRING,
    `fld` STRING,
    `is_error` STRING,
    `error_step` STRING,
    `error_info` STRING,
    `meta_data` STRING,
    `classify_info` STRING,
    `parse_html` STRING,
    `crawl_time` STRING
) PARTITIONED BY (`date_key` STRING)
STORED AS ORC
''')

spark.sql('''
INSERT INTO TABLE internal_platform_db.ai_engine_classify_parse_result_daily_pyspark_100 PARTITION (date_key='20260510')
VALUES
    ('cos1','http://www.example.com/p1','cos_u1','zh','内容页','t1','c1','2026-05-10','site1','at1','ct1','auth1','html1','0','tag1','www.example.com','example.com','0',NULL,NULL,'meta1','cls1','{"content":"This is a long enough content for testing purposes here"}','2026-05-10'),
    ('cos2','http://www.example.com/p2','cos_u2','zh','索引页','t2','c2','2026-05-10','site1','at2','ct2','auth2','html2','0','tag2','www.example.com','example.com','0',NULL,NULL,'meta2','cls2','{"content":"short"}','2026-05-10'),
    ('cos3','http://www.example.com/p3','cos_u3','zh','内容页','t3','c3','2026-05-10','site1','at3','ct3','auth3','html3','0','tag3','www.example.com','example.com','1','2','err info 3','meta3','cls3','{"content":""}','2026-05-10'),
    ('cos4','http://news.test.org/p1','cos_u4','en','内容页','t4','c4','2026-05-10','site2','at4','ct4','auth4','html4','0','tag4','news.test.org','test.org','0',NULL,NULL,'meta4','cls4','{"content":"Another long content that is definitely more than fifty characters total"}','2026-05-10'),
    ('cos5','http://news.test.org/p2','cos_u5','en','索引页','t5','c5','2026-05-10','site2','at5','ct5','auth5','html5','0','tag5','news.test.org','test.org','1','1','err info 5','meta5','cls5','{"content":""}','2026-05-10')
''')

spark.sql('''
INSERT INTO TABLE internal_platform_db.ai_engine_classify_parse_result_daily_pyspark_100 PARTITION (date_key='20260512')
VALUES
    ('cos6','http://blog.demo.net/p1','cos_u6','zh','内容页','t6','c6','2026-05-12','site3','at6','ct6','auth6','html6','0','tag6','blog.demo.net','demo.net','0',NULL,NULL,'meta6','cls6','{"content":"Blog post content that is long enough to pass the fifty char threshold easily"}','2026-05-12'),
    ('cos7','http://blog.demo.net/p2','cos_u7','zh','内容页','t7','c7','2026-05-12','site3','at7','ct7','auth7','html7','0','tag7','blog.demo.net','demo.net','1','3','err info 7','meta7','cls7','{"content":"x"}','2026-05-12'),
    ('cos8','http://www.example.com/p4','cos_u8','zh','索引页','t8','c8','2026-05-12','site1','at8','ct8','auth8','html8','0','tag8','www.example.com','example.com','0',NULL,NULL,'meta8','cls8','{"content":"ok content more than fifty chars to be safe and avoid short classification"}','2026-05-12')
''')

print('Database initialization complete')
spark.stop()