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251 lines
11 KiB
Python
251 lines
11 KiB
Python
#
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# Copyright 2015 LinkedIn Corp. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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#
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import json
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import os
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import sys
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from com.ziclix.python.sql import zxJDBC
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from metadata.etl.dataset.hive import HiveViewDependency
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from org.slf4j import LoggerFactory
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from wherehows.common import Constant
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from wherehows.common.schemas import DatasetSchemaRecord, DatasetFieldRecord, HiveDependencyInstanceRecord, \
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DatasetInstanceRecord
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from wherehows.common.writers import FileWriter
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import FileUtil
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from AvroColumnParser import AvroColumnParser
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from HiveColumnParser import HiveColumnParser
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from HiveExtract import TableInfo
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class HiveTransform:
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def __init__(self):
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self.logger = LoggerFactory.getLogger('jython script : ' + self.__class__.__name__)
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# connection
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username = args[Constant.HIVE_METASTORE_USERNAME]
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password = args[Constant.HIVE_METASTORE_PASSWORD]
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jdbc_driver = args[Constant.HIVE_METASTORE_JDBC_DRIVER]
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jdbc_url = args[Constant.HIVE_METASTORE_JDBC_URL]
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self.conn_hms = zxJDBC.connect(jdbc_url, username, password, jdbc_driver)
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self.curs = self.conn_hms.cursor()
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# variable
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self.dataset_dict = {}
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def transform(self, input, hive_instance, hive_metadata, hive_field_metadata, view_dependency):
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"""
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convert from json to csv
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:param input: input json file
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:param hive_instance: output data file for hive instance
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:param hive_metadata: output data file for hive table metadata
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:param hive_field_metadata: output data file for hive field metadata
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:return:
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"""
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all_data = []
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with open(input) as input_file:
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for line in input_file:
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all_data.append(json.loads(line))
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dataset_idx = -1
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instance_file_writer = FileWriter(hive_instance)
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schema_file_writer = FileWriter(hive_metadata)
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field_file_writer = FileWriter(hive_field_metadata)
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dependency_file_writer = FileWriter(view_dependency)
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depends_sql = """
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SELECT d.NAME DB_NAME, case when t.TBL_NAME regexp '_[0-9]+_[0-9]+_[0-9]+$'
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then concat(substring(t.TBL_NAME, 1, length(t.TBL_NAME) - length(substring_index(t.TBL_NAME, '_', -3)) - 1),'_{version}')
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else t.TBL_NAME
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end dataset_name,
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concat('/', d.NAME, '/', t.TBL_NAME) object_name,
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case when (d.NAME like '%\_mp' or d.NAME like '%\_mp\_versioned') and d.NAME not like 'dalitest%' and t.TBL_TYPE = 'VIRTUAL_VIEW'
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then 'dalids'
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else 'hive'
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end object_type,
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case when (d.NAME like '%\_mp' or d.NAME like '%\_mp\_versioned') and d.NAME not like 'dalitest%' and t.TBL_TYPE = 'VIRTUAL_VIEW'
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then 'View'
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else
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case when LOCATE('view', LOWER(t.TBL_TYPE)) > 0 then 'View'
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when LOCATE('index', LOWER(t.TBL_TYPE)) > 0 then 'Index'
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else 'Table'
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end
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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'
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then 'dalids'
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else 'hive'
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end prefix
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FROM TBLS t JOIN DBS d on t.DB_ID = d.DB_ID
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WHERE d.NAME = '{db_name}' and t.TBL_NAME = '{table_name}'
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"""
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# one db info : 'type', 'database', 'tables'
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# one table info : required : 'name' , 'type', 'serializationFormat' ,'createTime', 'DB_ID', 'TBL_ID', 'SD_ID'
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# optional : 'schemaLiteral', 'schemaUrl', 'fieldDelimiter', 'fieldList'
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for one_db_info in all_data:
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i = 0
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for table in one_db_info['tables']:
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i += 1
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schema_json = {}
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prop_json = {} # set the prop json
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for prop_name in TableInfo.optional_prop:
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if prop_name in table and table[prop_name] is not None:
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prop_json[prop_name] = table[prop_name]
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view_expanded_text = ''
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if TableInfo.view_expended_text in prop_json:
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view_expanded_text = prop_json[TableInfo.view_expended_text]
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text = prop_json[TableInfo.view_expended_text].replace('`', '') # this will be fixed after switching to Hive AST
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array = []
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try:
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array = HiveViewDependency.getViewDependency(text)
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except:
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self.logger.error("HiveViewDependency.getViewDependency(%s) failed!" % (table['name']))
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l = []
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for a in array:
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l.append(a)
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names = str(a).split('.')
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if names and len(names) >= 2:
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db_name = names[0].lower()
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table_name = names[1].lower()
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if db_name and table_name:
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self.curs.execute(depends_sql.format(db_name=db_name, table_name=table_name, version='{version}'))
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rows = self.curs.fetchall()
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self.conn_hms.commit()
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if rows and len(rows) > 0:
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for row_index, row_value in enumerate(rows):
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dependent_record = HiveDependencyInstanceRecord(
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one_db_info['type'],
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table['type'],
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"/%s/%s" % (one_db_info['database'], table['name']),
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'dalids:///' + one_db_info['database'] + '/' + table['dataset_name']
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if one_db_info['type'].lower() == 'dalids'
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else 'hive:///' + one_db_info['database'] + '/' + table['dataset_name'],
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'depends on',
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'Y',
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row_value[3],
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row_value[4],
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row_value[2],
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row_value[5] + ':///' + row_value[0] + '/' + row_value[1], '')
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dependency_file_writer.append(dependent_record)
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prop_json['view_depends_on'] = l
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dependency_file_writer.flush()
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# process either schema
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flds = {}
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field_detail_list = []
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if TableInfo.schema_literal in table and \
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table[TableInfo.schema_literal] is not None and \
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table[TableInfo.schema_literal].startswith('{'):
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sort_id = 0
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urn = "hive:///%s/%s" % (one_db_info['database'], table['dataset_name'])
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self.logger.info("Getting schema literal for: %s" % (urn))
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try:
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schema_data = json.loads(table[TableInfo.schema_literal])
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schema_json = schema_data
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acp = AvroColumnParser(schema_data, urn = urn)
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result = acp.get_column_list_result()
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field_detail_list += result
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except ValueError:
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self.logger.error("Schema Literal JSON error for table: " + str(table))
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elif TableInfo.field_list in table:
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# Convert to avro
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uri = "hive:///%s/%s" % (one_db_info['database'], table['dataset_name'])
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if one_db_info['type'].lower() == 'dalids':
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uri = "dalids:///%s/%s" % (one_db_info['database'], table['dataset_name'])
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else:
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uri = "hive:///%s/%s" % (one_db_info['database'], table['dataset_name'])
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self.logger.info("Getting column definition for: %s" % (uri))
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try:
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hcp = HiveColumnParser(table, urn = uri)
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schema_json = {'fields' : hcp.column_type_dict['fields'], 'type' : 'record', 'name' : table['name'], 'uri' : uri}
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field_detail_list += hcp.column_type_list
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except:
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self.logger.error("HiveColumnParser(%s) failed!" % (uri))
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schema_json = {'fields' : {}, 'type' : 'record', 'name' : table['name'], 'uri' : uri}
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if one_db_info['type'].lower() == 'dalids':
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dataset_urn = "dalids:///%s/%s" % (one_db_info['database'], table['dataset_name'])
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else:
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dataset_urn = "hive:///%s/%s" % (one_db_info['database'], table['dataset_name'])
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dataset_instance_record = DatasetInstanceRecord('dalids:///' + one_db_info['database'] + '/' + table['name']
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if one_db_info['type'].lower() == 'dalids'
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else 'hive:///' + one_db_info['database'] + '/' + table['name'],
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'grid',
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'',
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'',
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'*',
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True,
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table['native_name'],
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table['logical_name'],
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table['version'],
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table['create_time'],
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json.dumps(schema_json),
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json.dumps(view_expanded_text),
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dataset_urn)
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instance_file_writer.append(dataset_instance_record)
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if dataset_urn not in self.dataset_dict:
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dataset_scehma_record = DatasetSchemaRecord(table['dataset_name'], json.dumps(schema_json),
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json.dumps(prop_json),
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json.dumps(flds), dataset_urn, 'Hive', one_db_info['type'],
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table['type'], '',
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table.get(TableInfo.create_time),
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(int(table.get(TableInfo.source_modified_time,"0"))))
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schema_file_writer.append(dataset_scehma_record)
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dataset_idx += 1
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self.dataset_dict[dataset_urn] = dataset_idx
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for fields in field_detail_list:
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field_record = DatasetFieldRecord(fields)
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field_file_writer.append(field_record)
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instance_file_writer.flush()
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schema_file_writer.flush()
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field_file_writer.flush()
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self.logger.info("%20s contains %6d tables" % (one_db_info['database'], i))
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instance_file_writer.close()
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schema_file_writer.close()
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field_file_writer.close()
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dependency_file_writer.close()
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if __name__ == "__main__":
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args = sys.argv[1]
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t = HiveTransform()
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temp_dir = FileUtil.etl_temp_dir(args, "HIVE")
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schema_json_file = os.path.join(temp_dir, args[Constant.HIVE_SCHEMA_JSON_FILE_KEY])
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instance_csv_file = os.path.join(temp_dir, args[Constant.HIVE_INSTANCE_CSV_FILE_KEY])
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schema_csv_file = os.path.join(temp_dir, args[Constant.HIVE_SCHEMA_CSV_FILE_KEY])
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field_csv_file = os.path.join(temp_dir, args[Constant.HIVE_FIELD_METADATA_KEY])
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dependency_csv_file = os.path.join(temp_dir, args[Constant.HIVE_DEPENDENCY_CSV_FILE_KEY])
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try:
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t.transform(schema_json_file, instance_csv_file, schema_csv_file, field_csv_file, dependency_csv_file)
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finally:
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t.curs.close()
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t.conn_hms.close()
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