def transform(this, raw_metadata, metadata_output, field_metadata_output): input_json_file = open(raw_metadata, 'r') schema_file_writer = FileWriter(metadata_output) field_file_writer = FileWriter(field_metadata_output) i = 0 this.sort_id = 0 o_urn = '' for line in input_json_file: try: j = json.loads(line) except: this.logger.error(" Invalid JSON:\n%s" % line) continue i += 1 o_field_list_ = [] this.sort_id = 0 if not j.has_key('attributes'): o_properties = {"doc": null} else: o_properties = dict(j['attributes'].items()) del j['attributes'] if j.has_key('uri'): o_urn = j['uri'] o_name = o_urn[o_urn.rfind('/') + 1:] o_source = 'Hbase' else: this.logger.info('*** Warning: "uri" is not found in %s' % j['name']) o_urn = '' o_name = '' if not j.has_key('fields'): o_fields = {"doc": None} else: o_fields = {} for f in j['fields']: o_field_name = f['name'] o_fields[o_field_name] = dict(f) acp = AvroColumnParser(j, o_urn) o_field_list_ += acp.get_column_list_result() dataset_schema_record = DatasetSchemaRecord( o_name, json.dumps(j, sort_keys=True), json.dumps(o_properties, sort_keys=True), json.dumps(o_fields), o_urn, o_source, 'HBase', 'Table', None, None, None) schema_file_writer.append(dataset_schema_record) for fields in o_field_list_: field_record = DatasetFieldRecord(fields) field_file_writer.append(field_record) field_file_writer.close() schema_file_writer.close() input_json_file.close()
def test_parse_complex(self): avro_json = json.loads(sample_avro_with_complex_field) acp = AvroColumnParser(avro_json) result = acp.get_column_list_result() self.assertEqual(result, expect_result)
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() # 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) prop_json['view_depends_on'] = l # process either schema flds = {} field_detail_list = [] if TableInfo.schema_literal in table and table[ TableInfo.schema_literal] is not None: sort_id = 0 try: schema_data = json.loads( table[TableInfo.schema_literal]) except ValueError: self.logger.error("Schema json error for table : \n" + str(table)) schema_json = schema_data # extract fields to field record urn = "hive:///%s/%s" % (one_db_info['database'], table['name']) acp = AvroColumnParser(schema_data, urn=urn) result = acp.get_column_list_result() field_detail_list += result elif TableInfo.field_list in table: # Convert to avro uri = "hive:///%s/%s" % (one_db_info['database'], table['name']) hcp = HiveColumnParser(table, urn=uri) schema_json = { 'fields': hcp.column_type_dict['fields'], 'type': 'record', 'name': table['name'], 'uri': uri } field_detail_list += hcp.column_type_list dataset_scehma_record = DatasetSchemaRecord( table['name'], json.dumps(schema_json), json.dumps(prop_json), json.dumps(flds), "hive:///%s/%s" % (one_db_info['database'], table['name']), 'Hive', '', (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)) schema_file_writer.close() field_file_writer.close()
def transform(self, input, hive_instance, 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: """ all_data = [] with open(input) as input_file: for line in input_file: all_data.append(json.loads(line)) dataset_idx = -1 instance_file_writer = FileWriter(hive_instance) 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 'dalids' 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, 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}' """ # 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] view_expanded_text = '' if TableInfo.view_expended_text in prop_json: view_expanded_text = prop_json[ TableInfo.view_expended_text] text = prop_json[TableInfo.view_expended_text].replace( '`', '') # this will be fixed after switching to Hive AST array = [] try: array = HiveViewDependency.getViewDependency(text) except: self.logger.error( "HiveViewDependency.getViewDependency(%s) failed!" % (table['name'])) l = [] for a in array: l.append(a) names = str(a).split('.') if names and len(names) >= 2: db_name = names[0].lower() table_name = names[1].lower() if db_name and table_name: self.curs.execute( depends_sql.format(db_name=db_name, table_name=table_name, version='{version}')) rows = self.curs.fetchall() self.conn_hms.commit() 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['dataset_name'] if one_db_info['type'].lower() == 'dalids' else 'hive:///' + one_db_info['database'] + '/' + table['dataset_name'], 'depends on', 'Y', row_value[3], row_value[4], row_value[2], row_value[5] + ':///' + row_value[0] + '/' + row_value[1], '') self.instance_writer.append( dependent_record) prop_json['view_depends_on'] = l self.instance_writer.flush() # process either schema flds = {} field_detail_list = [] if TableInfo.schema_literal in table and \ table[TableInfo.schema_literal] is not None and \ table[TableInfo.schema_literal].startswith('{'): sort_id = 0 urn = "hive:///%s/%s" % (one_db_info['database'], table['dataset_name']) self.logger.info("Getting schema literal for: %s" % (urn)) try: schema_data = json.loads( table[TableInfo.schema_literal]) schema_json = schema_data acp = AvroColumnParser(schema_data, urn=urn) result = acp.get_column_list_result() field_detail_list += result except ValueError: self.logger.error( "Schema Literal JSON error for table: " + str(table)) elif TableInfo.field_list in table: # Convert to avro uri = "hive:///%s/%s" % (one_db_info['database'], table['dataset_name']) if one_db_info['type'].lower() == 'dalids': uri = "dalids:///%s/%s" % (one_db_info['database'], table['dataset_name']) else: uri = "hive:///%s/%s" % (one_db_info['database'], table['dataset_name']) self.logger.info("Getting column definition for: %s" % (uri)) try: hcp = HiveColumnParser(table, urn=uri) schema_json = { 'fields': hcp.column_type_dict['fields'], 'type': 'record', 'name': table['name'], 'uri': uri } field_detail_list += hcp.column_type_list except: self.logger.error("HiveColumnParser(%s) failed!" % (uri)) schema_json = { 'fields': {}, 'type': 'record', 'name': table['name'], 'uri': uri } if one_db_info['type'].lower() == 'dalids': dataset_urn = "dalids:///%s/%s" % (one_db_info['database'], table['dataset_name']) else: dataset_urn = "hive:///%s/%s" % (one_db_info['database'], table['dataset_name']) dataset_instance_record = DatasetInstanceRecord( 'dalids:///' + one_db_info['database'] + '/' + table['name'] if one_db_info['type'].lower() == 'dalids' else 'hive:///' + one_db_info['database'] + '/' + table['name'], 'grid', '', '', '*', 0, table['native_name'], table['logical_name'], table['version'], table['create_time'], json.dumps(schema_json), json.dumps(view_expanded_text), dataset_urn) instance_file_writer.append(dataset_instance_record) if dataset_urn not in self.dataset_dict: dataset_scehma_record = DatasetSchemaRecord( table['dataset_name'], json.dumps(schema_json), json.dumps(prop_json), json.dumps(flds), dataset_urn, 'Hive', one_db_info['type'], table['type'], '', table.get(TableInfo.create_time), (int(table.get(TableInfo.source_modified_time, "0")))) schema_file_writer.append(dataset_scehma_record) dataset_idx += 1 self.dataset_dict[dataset_urn] = dataset_idx for fields in field_detail_list: field_record = DatasetFieldRecord(fields) field_file_writer.append(field_record) instance_file_writer.flush() schema_file_writer.flush() field_file_writer.flush() self.logger.info("%20s contains %6d tables" % (one_db_info['database'], i)) instance_file_writer.close() schema_file_writer.close() field_file_writer.close()
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 'dalids' 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, 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}' """ # 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'] 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) prop_json['view_depends_on'] = l self.instance_writer.flush() # process either schema flds = {} field_detail_list = [] if TableInfo.schema_literal in table and table[TableInfo.schema_literal] is not None: sort_id = 0 urn = "hive:///%s/%s" % (one_db_info['database'], table['name']) try: schema_data = json.loads(table[TableInfo.schema_literal]) schema_json = schema_data acp = AvroColumnParser(schema_data, urn = urn) result = acp.get_column_list_result() field_detail_list += result except ValueError: self.logger.error("Schema json error for table : \n" + str(table)) elif TableInfo.field_list in table: # Convert to avro uri = "hive:///%s/%s" % (one_db_info['database'], table['name']) if one_db_info['type'].lower() == 'dalids': uri = "dalids:///%s/%s" % (one_db_info['database'], table['name']) else: uri = "hive:///%s/%s" % (one_db_info['database'], table['name']) hcp = HiveColumnParser(table, urn = uri) schema_json = {'fields' : hcp.column_type_dict['fields'], 'type' : 'record', 'name' : table['name'], 'uri' : uri} field_detail_list += hcp.column_type_list if one_db_info['type'].lower() == 'dalids': dataset_urn = "dalids:///%s/%s" % (one_db_info['database'], table['name']) else: dataset_urn = "hive:///%s/%s" % (one_db_info['database'], table['name']) 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'], '', (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)) schema_file_writer.close() field_file_writer.close()
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() # 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) prop_json['view_depends_on'] = l # process either schema flds = {} field_detail_list = [] if TableInfo.schema_literal in table and table[TableInfo.schema_literal] is not None: sort_id = 0 urn = "hive:///%s/%s" % (one_db_info['database'], table['name']) try: schema_data = json.loads(table[TableInfo.schema_literal]) schema_json = schema_data acp = AvroColumnParser(schema_data, urn = urn) result = acp.get_column_list_result() field_detail_list += result except ValueError: self.logger.error("Schema json error for table : \n" + str(table)) elif TableInfo.field_list in table: # Convert to avro uri = "hive:///%s/%s" % (one_db_info['database'], table['name']) hcp = HiveColumnParser(table, urn = uri) schema_json = {'fields' : hcp.column_type_dict['fields'], 'type' : 'record', 'name' : table['name'], 'uri' : uri} field_detail_list += hcp.column_type_list dataset_scehma_record = DatasetSchemaRecord(table['name'], json.dumps(schema_json), json.dumps(prop_json), json.dumps(flds), "hive:///%s/%s" % (one_db_info['database'], table['name']), 'Hive', '', (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)) schema_file_writer.close() field_file_writer.close()
def transform(self, input, hive_instance, hive_metadata, hive_field_metadata, view_dependency): """ convert from json to csv :param input: input json file :param hive_instance: output data file for hive instance :param hive_metadata: output data file for hive table metadata :param hive_field_metadata: output data file for hive field metadata :return: """ all_data = [] with open(input) as input_file: for line in input_file: all_data.append(json.loads(line)) dataset_idx = -1 instance_file_writer = FileWriter(hive_instance) schema_file_writer = FileWriter(hive_metadata) field_file_writer = FileWriter(hive_field_metadata) dependency_file_writer = FileWriter(view_dependency) 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 'dalids' 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, 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}' """ # 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] view_expanded_text = '' if TableInfo.view_expended_text in prop_json: view_expanded_text = prop_json[TableInfo.view_expended_text] text = prop_json[TableInfo.view_expended_text].replace('`', '') # this will be fixed after switching to Hive AST array = [] try: array = HiveViewDependency.getViewDependency(text) except: self.logger.error("HiveViewDependency.getViewDependency(%s) failed!" % (table['name'])) l = [] for a in array: l.append(a) names = str(a).split('.') if names and len(names) >= 2: db_name = names[0].lower() table_name = names[1].lower() if db_name and table_name: self.curs.execute(depends_sql.format(db_name=db_name, table_name=table_name, version='{version}')) rows = self.curs.fetchall() self.conn_hms.commit() 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['dataset_name'] if one_db_info['type'].lower() == 'dalids' else 'hive:///' + one_db_info['database'] + '/' + table['dataset_name'], 'depends on', 'Y', row_value[3], row_value[4], row_value[2], row_value[5] + ':///' + row_value[0] + '/' + row_value[1], '') dependency_file_writer.append(dependent_record) prop_json['view_depends_on'] = l dependency_file_writer.flush() # process either schema flds = {} field_detail_list = [] if TableInfo.schema_literal in table and \ table[TableInfo.schema_literal] is not None and \ table[TableInfo.schema_literal].startswith('{'): sort_id = 0 urn = "hive:///%s/%s" % (one_db_info['database'], table['dataset_name']) self.logger.info("Getting schema literal for: %s" % (urn)) try: schema_data = json.loads(table[TableInfo.schema_literal]) schema_json = schema_data acp = AvroColumnParser(schema_data, urn = urn) result = acp.get_column_list_result() field_detail_list += result except ValueError: self.logger.error("Schema Literal JSON error for table: " + str(table)) elif TableInfo.field_list in table: # Convert to avro uri = "hive:///%s/%s" % (one_db_info['database'], table['dataset_name']) if one_db_info['type'].lower() == 'dalids': uri = "dalids:///%s/%s" % (one_db_info['database'], table['dataset_name']) else: uri = "hive:///%s/%s" % (one_db_info['database'], table['dataset_name']) self.logger.info("Getting column definition for: %s" % (uri)) try: hcp = HiveColumnParser(table, urn = uri) schema_json = {'fields' : hcp.column_type_dict['fields'], 'type' : 'record', 'name' : table['name'], 'uri' : uri} field_detail_list += hcp.column_type_list except: self.logger.error("HiveColumnParser(%s) failed!" % (uri)) schema_json = {'fields' : {}, 'type' : 'record', 'name' : table['name'], 'uri' : uri} if one_db_info['type'].lower() == 'dalids': dataset_urn = "dalids:///%s/%s" % (one_db_info['database'], table['dataset_name']) else: dataset_urn = "hive:///%s/%s" % (one_db_info['database'], table['dataset_name']) dataset_instance_record = DatasetInstanceRecord('dalids:///' + one_db_info['database'] + '/' + table['name'] if one_db_info['type'].lower() == 'dalids' else 'hive:///' + one_db_info['database'] + '/' + table['name'], 'grid', '', '', '*', True, table['native_name'], table['logical_name'], table['version'], table['create_time'], json.dumps(schema_json), json.dumps(view_expanded_text), dataset_urn) instance_file_writer.append(dataset_instance_record) if dataset_urn not in self.dataset_dict: dataset_scehma_record = DatasetSchemaRecord(table['dataset_name'], json.dumps(schema_json), json.dumps(prop_json), json.dumps(flds), dataset_urn, 'Hive', one_db_info['type'], table['type'], '', table.get(TableInfo.create_time), (int(table.get(TableInfo.source_modified_time,"0")))) schema_file_writer.append(dataset_scehma_record) dataset_idx += 1 self.dataset_dict[dataset_urn] = dataset_idx for fields in field_detail_list: field_record = DatasetFieldRecord(fields) field_file_writer.append(field_record) instance_file_writer.flush() schema_file_writer.flush() field_file_writer.flush() self.logger.info("%20s contains %6d tables" % (one_db_info['database'], i)) instance_file_writer.close() schema_file_writer.close() field_file_writer.close() dependency_file_writer.close()
def transform(self, raw_metadata, metadata_output, field_metadata_output): # sys.setdefaultencoding("UTF-8") input_json_file = open(raw_metadata, 'r') schema_file_writer = FileWriter(metadata_output) field_file_writer = FileWriter(field_metadata_output) i = 0 self.sort_id = 0 o_urn = '' p = '' for line in input_json_file: try: j = json.loads(line) except: self.logger.error(" Invalid JSON:\n%s" % line) continue i += 1 o_field_list_ = [] parent_field_path = '' self.sort_id = 0 if not (j.has_key('attributes_json') or j.has_key('attributes')): o_properties = {"doc": null} else: o_properties = {} if j.has_key('attributes_json'): o_properties = json.loads(j['attributes_json']) del j['attributes_json'] if j.has_key('attributes'): o_properties = dict(j['attributes'].items() + o_properties.items()) del j['attributes'] if j.has_key('uri'): o_urn = j['uri'] elif o_properties.has_key('uri'): o_urn = o_properties['uri'] else: self.logger.info('*** Warning: "uri" is not found in %s' % j['name']) o_urn = '' if o_urn.find('hdfs://') == 0: o_name = o_urn[o_urn.rfind('/') + 1:] elif o_properties.has_key('table_name'): o_name = o_properties['table_name'] elif j.has_key('name') and j['name'][0:5] != 'TUPLE': o_name = j['name'] else: o_name = o_urn[o_urn.rfind('/') + 1:] if j.has_key('id') or not j.has_key('fields'): # esWritable schema o_fields = {} for k in j: if not (k == 'uri' or k == 'attributes' or k == 'doc'): if type(j[k]) == list: o_fields[k] = { "name": k, "type": 'list', "doc": str(j[k]) } elif type(j[k]) == dict: o_fields[k] = { "name": k, "type": 'dict', "doc": str(j[k]) } else: o_fields[k] = { "name": k, "type": j[k], "doc": None } self.sort_id += 1 o_field_list_.append([ o_urn, self.sort_id, 0, '', k, o_fields[k]['type'], '', '', '', o_fields[k]['doc'].replace("\n", ' ') if o_fields[k]['doc'] is not None else None ]) elif j.has_key('fields'): o_fields = {} for f in j['fields']: o_field_name = f['name'] o_fields[o_field_name] = dict(f) # for schema output if f.has_key('attributes_json'): f['attributes'] = json.loads(f['attributes_json']) del f['attributes_json'] acp = AvroColumnParser(j, o_urn) o_field_list_ += acp.get_column_list_result() else: o_fields = {"doc": None} if j.has_key('attributes') and not o_properties.has_key('source'): o_properties['source'] = j['attributes']['source'] if o_urn.startswith( 'hdfs:///') and self.file_regex_source_map is not None: o_source = self.get_source(o_urn[7:]) else: self.logger.warn( "property : " + Constant.HDFS_FILE_SOURCE_MAP_KEY + " is None, will use default source for all dataset") o_source = 'Hdfs' self.logger.info( "%4i (%6i): %4i fields, %4i total fields(including nested) found in [%s]@%s with source %s" % (i, len(j), len(o_fields), len(o_field_list_), o_name, o_urn, o_source)) dataset_schema_record = DatasetSchemaRecord( o_name, json.dumps(j, sort_keys=True), json.dumps(o_properties, sort_keys=True), json.dumps(o_fields), o_urn, o_source, None, None, None) schema_file_writer.append(dataset_schema_record) for fields in o_field_list_: field_record = DatasetFieldRecord(fields) field_file_writer.append(field_record) schema_file_writer.close() field_file_writer.close() input_json_file.close()