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#
# Copyright 2015 LinkedIn Corp. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#
import json
import datetime
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import sys, os
import time
from com.ziclix.python.sql import zxJDBC
from org.slf4j import LoggerFactory
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from wherehows.common.writers import FileWriter
from wherehows.common.schemas import DatasetSchemaRecord, DatasetFieldRecord, HiveDependencyInstanceRecord
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from wherehows.common import Constant
from HiveExtract import TableInfo
from org.apache.hadoop.hive.ql.tools import LineageInfo
from metadata.etl.dataset.hive import HiveViewDependency
from HiveColumnParser import HiveColumnParser
from AvroColumnParser import AvroColumnParser
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class HiveTransform:
def __init__(self):
self.logger = LoggerFactory.getLogger('jython script : ' + self.__class__.__name__)
username = args[Constant.HIVE_METASTORE_USERNAME]
password = args[Constant.HIVE_METASTORE_PASSWORD]
jdbc_driver = args[Constant.HIVE_METASTORE_JDBC_DRIVER]
jdbc_url = args[Constant.HIVE_METASTORE_JDBC_URL]
self.conn_hms = zxJDBC.connect(jdbc_url, username, password, jdbc_driver)
self.curs = self.conn_hms.cursor()
dependency_instance_file = args[Constant.HIVE_DEPENDENCY_CSV_FILE_KEY]
self.instance_writer = FileWriter(dependency_instance_file)
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def transform(self, input, hive_metadata, hive_field_metadata):
"""
convert from json to csv
:param input: input json file
:param hive_metadata: output data file for hive table metadata
:param hive_field_metadata: output data file for hive field metadata
:return:
"""
f_json = open(input)
all_data = json.load(f_json)
f_json.close()
schema_file_writer = FileWriter(hive_metadata)
field_file_writer = FileWriter(hive_field_metadata)
lineageInfo = LineageInfo()
depends_sql = """
SELECT d.NAME DB_NAME, case when t.TBL_NAME regexp '_[0-9]+_[0-9]+_[0-9]+$'
then concat(substring(t.TBL_NAME, 1, length(t.TBL_NAME) - length(substring_index(t.TBL_NAME, '_', -3)) - 1),'_{version}')
else t.TBL_NAME
end dataset_name,
concat('/', d.NAME, '/', t.TBL_NAME) object_name,
case when (d.NAME like '%\_mp' or d.NAME like '%\_mp\_versioned') and d.NAME not like 'dalitest%' and t.TBL_TYPE = 'VIRTUAL_VIEW'
then 'Dali'
else 'Hive'
end object_type,
case when (d.NAME like '%\_mp' or d.NAME like '%\_mp\_versioned') and d.NAME not like 'dalitest%' and t.TBL_TYPE = 'VIRTUAL_VIEW'
then 'View'
else
case when LOCATE('view', LOWER(t.TBL_TYPE)) > 0 then 'View'
when LOCATE('index', LOWER(t.TBL_TYPE)) > 0 then 'Index'
else 'Table'
end
end object_sub_type,
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case when (d.NAME like '%\_mp' or d.NAME like '%\_mp\_versioned') and t.TBL_TYPE = 'VIRTUAL_VIEW'
then 'dalids'
else 'hive'
end prefix
FROM TBLS t JOIN DBS d on t.DB_ID = d.DB_ID
WHERE d.NAME = '{db_name}' and t.TBL_NAME = '{table_name}'
"""
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# one db info : 'type', 'database', 'tables'
# one table info : required : 'name' , 'type', 'serializationFormat' ,'createTime', 'DB_ID', 'TBL_ID', 'SD_ID'
# optional : 'schemaLiteral', 'schemaUrl', 'fieldDelimiter', 'fieldList'
for one_db_info in all_data:
i = 0
for table in one_db_info['tables']:
i += 1
schema_json = {}
prop_json = {} # set the prop json
for prop_name in TableInfo.optional_prop:
if prop_name in table and table[prop_name] is not None:
prop_json[prop_name] = table[prop_name]
if TableInfo.view_expended_text in prop_json:
text = prop_json[TableInfo.view_expended_text].replace('`', '')
array = HiveViewDependency.getViewDependency(text)
l = []
for a in array:
l.append(a)
names = str(a).split('.')
if names and len(names) >= 2:
db_name = names[0]
table_name = names[1]
if db_name and table_name:
rows = []
self.curs.execute(depends_sql.format(db_name=db_name, table_name=table_name, version='{version}'))
rows = self.curs.fetchall()
if rows and len(rows) > 0:
for row_index, row_value in enumerate(rows):
dependent_record = HiveDependencyInstanceRecord(
one_db_info['type'],
table['type'],
"/%s/%s" % (one_db_info['database'], table['name']),
'dalids:///' + one_db_info['database'] + '/' + table['name']
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if one_db_info['type'].lower() == 'dalids'
else 'hive:///' + one_db_info['database'] + '/' + table['name'],
'depends on',
'is used by',
row_value[3],
row_value[4],
row_value[2],
row_value[5] + ':///' + row_value[0] + '/' + row_value[1], '')
self.instance_writer.append(dependent_record)
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prop_json['view_depends_on'] = l
self.instance_writer.flush()
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# process either schema
flds = {}
field_detail_list = []
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if TableInfo.schema_literal in table and table[TableInfo.schema_literal] is not None:
sort_id = 0
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urn = "hive:///%s/%s" % (one_db_info['database'], table['name'])
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try:
schema_data = json.loads(table[TableInfo.schema_literal])
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schema_json = schema_data
acp = AvroColumnParser(schema_data, urn = urn)
result = acp.get_column_list_result()
field_detail_list += result
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except ValueError:
self.logger.error("Schema json error for table : \n" + str(table))
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elif TableInfo.field_list in table:
# Convert to avro
uri = "hive:///%s/%s" % (one_db_info['database'], table['name'])
hcp = HiveColumnParser(table, urn = uri)
if one_db_info['type'].lower() == 'dali':
uri = "dalids:///%s/%s" % (one_db_info['database'], table['name'])
else:
uri = "hive:///%s/%s" % (one_db_info['database'], table['name'])
schema_json = {'fields' : hcp.column_type_dict['fields'], 'type' : 'record', 'name' : table['name'], 'uri' : uri}
field_detail_list += hcp.column_type_list
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if one_db_info['type'].lower() == 'dali':
dataset_urn = "dalids:///%s/%s" % (one_db_info['database'], table['name'])
else:
dataset_urn = "hive:///%s/%s" % (one_db_info['database'], table['name'])
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dataset_scehma_record = DatasetSchemaRecord(table['name'], json.dumps(schema_json), json.dumps(prop_json),
json.dumps(flds),
dataset_urn,
'Hive', one_db_info['type'], table['type'],
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'', (table[TableInfo.create_time] if table.has_key(
TableInfo.create_time) else None), (table["lastAlterTime"]) if table.has_key("lastAlterTime") else None)
schema_file_writer.append(dataset_scehma_record)
for fields in field_detail_list:
field_record = DatasetFieldRecord(fields)
field_file_writer.append(field_record)
schema_file_writer.flush()
field_file_writer.flush()
self.logger.info("%20s contains %6d tables" % (one_db_info['database'], i))
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schema_file_writer.close()
field_file_writer.close()
def convert_timestamp(self, time_string):
return int(time.mktime(time.strptime(time_string, "%Y-%m-%d %H:%M:%S")))
if __name__ == "__main__":
args = sys.argv[1]
t = HiveTransform()
try:
t.transform(args[Constant.HIVE_SCHEMA_JSON_FILE_KEY],
args[Constant.HIVE_SCHEMA_CSV_FILE_KEY],
args[Constant.HIVE_FIELD_METADATA_KEY])
finally:
t.curs.close()
t.conn_hms.close()
t.instance_writer.close()
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