def test_parse_simple_select_with_table_schema_prefix_and_extra_whitespace():
sql_meta = SqlParser.parse(
'''
SELECT *
FROM schema0.table0 ;
'''
)
assert sql_meta.in_tables == [DbTableName('schema0.table0')]
assert sql_meta.out_tables == []
def test_parse_simple_insert_into():
sql_meta = SqlParser.parse(
'''
INSERT INTO table0 (col0, col1, col2)
VALUES (val0, val1, val2);
'''
)
assert sql_meta.in_tables == []
assert sql_meta.out_tables == [DbTableName('table0')]
def test_parse_simple_select():
sql_meta = SqlParser.parse(
'''
SELECT *
FROM table0;
'''
)
log.debug("sqlparser.parse() successful.")
assert sql_meta.in_tables == [DbTableName('table0')]
assert sql_meta.out_tables == []
def test_parse_recursive_cte():
sql_meta = SqlParser.parse(
'''
WITH RECURSIVE subordinates AS
(SELECT employee_id,
manager_id,
full_name
FROM employees
WHERE employee_id = 2
UNION SELECT e.employee_id,
e.manager_id,
e.full_name
FROM employees e
INNER JOIN subordinates s ON s.employee_id = e.manager_id)
INSERT INTO sub_employees (employee_id, manager_id, full_name)
SELECT employee_id, manager_id, full_name FROM subordinates;
'''
)
assert sql_meta.in_tables == [DbTableName('employees')]
assert sql_meta.out_tables == [DbTableName('sub_employees')]
def _get_table(self, table: str, client: bigquery.Client) -> DbTableSchema:
bq_table = client.get_table(table)
if not bq_table._properties:
return
table = bq_table._properties
if not table.get('schema') or not table.get('schema').get('fields'):
return
fields = table.get('schema').get('fields')
columns = [
DbColumn(name=fields[i].get('name'),
type=fields[i].get('type'),
description=fields[i].get('description'),
ordinal_position=i) for i in range(len(fields))
]
self.log.info(DbTableName(table.get('tableReference').get('tableId')))
return DbTableSchema(
schema_name=table.get('tableReference').get('projectId') + '.' +
table.get('tableReference').get('datasetId'),
table_name=DbTableName(table.get('tableReference').get('tableId')),
columns=columns)
def test_parser_integration():
sql_meta = SqlParser.parse(
"""
INSERT INTO popular_orders_day_of_week (order_day_of_week, order_placed_on,orders_placed)
SELECT EXTRACT(ISODOW FROM order_placed_on) AS order_day_of_week,
order_placed_on,
COUNT(*) AS orders_placed
FROM top_delivery_times
GROUP BY order_placed_on;
""",
"public"
)
assert sql_meta.in_tables == [DbTableName('public.top_delivery_times')]
def _get_table(tokens, idx):
idx, token = tokens.token_next(idx=idx)
token_list = token.flatten()
table_name = next(token_list).value
try:
# Determine if the table contains the schema
# separated by a dot (format: 'schema.table')
dot = next(token_list)
if dot.match(Punctuation, '.'):
table_name += dot.value
table_name += next(token_list).value
except StopIteration:
pass
return idx, DbTableName(table_name)
def _get_table_schemas(self,
table_names: [DbTableName]) -> [DbTableSchema]:
# Avoid querying postgres by returning an empty array
# if no table names have been provided.
if not table_names:
return []
# Keeps tack of the schema by table.
schemas_by_table = {}
hook = PostgresHook(postgres_conn_id=self.operator.postgres_conn_id,
schema=self.operator.database)
with closing(hook.get_conn()) as conn:
with closing(conn.cursor()) as cursor:
table_names_as_list = ",".join(
map(lambda name: f"'{name}'", table_names))
cursor.execute(f"""
SELECT table_schema,
table_name,
column_name,
ordinal_position,
udt_name
FROM information_schema.columns
WHERE table_name IN ({table_names_as_list});
""")
for row in cursor.fetchall():
table_schema_name: str = row[_TABLE_SCHEMA]
table_name: DbTableName = DbTableName(row[_TABLE_NAME])
table_column: DbColumn = DbColumn(
name=row[_COLUMN_NAME],
type=row[_UDT_NAME],
ordinal_position=row[_ORDINAL_POSITION])
# Attempt to get table schema
table_key: str = f"{table_schema_name}.{table_name}"
table_schema: Optional[DbTableSchema] = \
schemas_by_table.get(table_key)
if table_schema:
# Add column to existing table schema.
schemas_by_table[table_key]. \
columns.append(table_column)
else:
# Create new table schema with column.
schemas_by_table[table_key] = DbTableSchema(
schema_name=table_schema_name,
table_name=table_name,
columns=[table_column])
return list(schemas_by_table.values())
def _get_tables(
tokens,
idx,
default_schema: Optional[str] = None) -> Tuple[int, List[DbTableName]]:
# Extract table identified by preceding SQL keyword at '_is_in_table'
def parse_ident(ident: Identifier) -> str:
# Extract table name from possible schema.table naming
token_list = ident.flatten()
table_name = next(token_list).value
try:
# Determine if the table contains the schema
# separated by a dot (format: 'schema.table')
dot = next(token_list)
if dot.match(Punctuation, '.'):
table_name += dot.value
table_name += next(token_list).value
elif default_schema:
table_name = f'{default_schema}.{table_name}'
except StopIteration:
if default_schema:
table_name = f'{default_schema}.{table_name}'
return table_name
idx, token = tokens.token_next(idx=idx)
tables = []
if isinstance(token, IdentifierList):
# Handle "comma separated joins" as opposed to explicit JOIN keyword
gidx = 0
tables.append(
parse_ident(token.token_first(skip_ws=True, skip_cm=True)))
gidx, punc = token.token_next(gidx, skip_ws=True, skip_cm=True)
while punc and punc.value == ',':
gidx, name = token.token_next(gidx, skip_ws=True, skip_cm=True)
tables.append(parse_ident(name))
gidx, punc = token.token_next(gidx)
else:
tables.append(parse_ident(token))
return idx, [DbTableName(table) for table in tables]
def test_tpcds_cte_query():
sql_meta = SqlParser.parse("""
WITH year_total AS
(SELECT c_customer_id customer_id,
c_first_name customer_first_name,
c_last_name customer_last_name,
c_preferred_cust_flag customer_preferred_cust_flag,
c_birth_country customer_birth_country,
c_login customer_login,
c_email_address customer_email_address,
d_year dyear,
Sum(((ss_ext_list_price - ss_ext_wholesale_cost - ss_ext_discount_amt)
+ ss_ext_sales_price) / 2) year_total,
's' sale_type
FROM src.customer,
store_sales,
date_dim
WHERE c_customer_sk = ss_customer_sk
AND ss_sold_date_sk = d_date_sk GROUP BY c_customer_id,
c_first_name,
c_last_name,
c_preferred_cust_flag,
c_birth_country,
c_login,
c_email_address,
d_year)
SELECT t_s_secyear.customer_id,
t_s_secyear.customer_first_name,
t_s_secyear.customer_last_name,
t_s_secyear.customer_preferred_cust_flag
FROM year_total t_s_firstyear,
year_total t_s_secyear,
year_total t_c_firstyear,
year_total t_c_secyear,
year_total t_w_firstyear,
year_total t_w_secyear
WHERE t_s_secyear.customer_id = t_s_firstyear.customer_id
AND t_s_firstyear.customer_id = t_c_secyear.customer_id
AND t_s_firstyear.customer_id = t_c_firstyear.customer_id
AND t_s_firstyear.customer_id = t_w_firstyear.customer_id
AND t_s_firstyear.customer_id = t_w_secyear.customer_id
AND t_s_firstyear.sale_type = 's'
AND t_c_firstyear.sale_type = 'c'
AND t_w_firstyear.sale_type = 'w'
AND t_s_secyear.sale_type = 's'
AND t_c_secyear.sale_type = 'c'
AND t_w_secyear.sale_type = 'w'
AND t_s_firstyear.dyear = 2001
AND t_s_secyear.dyear = 2001 + 1
AND t_c_firstyear.dyear = 2001
AND t_c_secyear.dyear = 2001 + 1
AND t_w_firstyear.dyear = 2001
AND t_w_secyear.dyear = 2001 + 1
AND t_s_firstyear.year_total > 0
AND t_c_firstyear.year_total > 0
AND t_w_firstyear.year_total > 0
AND CASE WHEN
t_c_firstyear.year_total > 0 THEN t_c_secyear.year_total / t_c_firstyear.year_total
ELSE NULL
END > CASE WHEN
t_s_firstyear.year_total > 0 THEN t_s_secyear.year_total / t_s_firstyear.year_total
ELSE NULL
END
AND CASE WHEN
t_c_firstyear.year_total > 0 THEN t_c_secyear.year_total / t_c_firstyear.year_total
ELSE NULL
END > CASE WHEN
t_w_firstyear.year_total > 0 THEN t_w_secyear.year_total / t_w_firstyear.year_total
ELSE NULL
END
ORDER BY t_s_secyear.customer_id,
t_s_secyear.customer_first_name,
t_s_secyear.customer_last_name,
t_s_secyear.customer_preferred_cust_flag
LIMIT 100;
""")
assert set(sql_meta.in_tables) == {
DbTableName("src.customer"),
DbTableName("store_sales"),
DbTableName("date_dim")
}
assert len(sql_meta.out_tables) == 0
import mock
from airflow.hooks.postgres_hook import PostgresHook
from airflow.operators.postgres_operator import PostgresOperator
from airflow.utils.dates import days_ago
from marquez_airflow import DAG
from marquez_airflow.models import (DbTableName, DbTableSchema, DbColumn)
from marquez_airflow.extractors import Source, Dataset, DatasetType
from marquez_airflow.extractors.postgres_extractor import PostgresExtractor
CONN_ID = 'food_delivery_db'
CONN_URI = 'postgres://localhost:5432/food_delivery'
DB_SCHEMA_NAME = 'public'
DB_TABLE_NAME = DbTableName('discounts')
DB_TABLE_COLUMNS = [
DbColumn(name='id', type='int4', ordinal_position=1),
DbColumn(name='amount_off', type='int4', ordinal_position=2),
DbColumn(name='customer_email', type='varchar', ordinal_position=3),
DbColumn(name='starts_on', type='timestamp', ordinal_position=4),
DbColumn(name='ends_on', type='timestamp', ordinal_position=5)
]
DB_TABLE_SCHEMA = DbTableSchema(schema_name=DB_SCHEMA_NAME,
table_name=DB_TABLE_NAME,
columns=DB_TABLE_COLUMNS)
NO_DB_TABLE_SCHEMA = []
SQL = f"SELECT * FROM {DB_TABLE_NAME.name};"
DAG_ID = 'email_discounts'