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
# process each field
for field in schema_data['fields']:
field_name = field['name']
type = field['type'] # could be a list
default_value = field[
'default'] if 'default' in field else None
doc = field['doc'] if 'doc' in field else None
attributes_json = json.loads(
field['attributes_json']
) if 'attributes_json' in field else None
pk = delta = is_nullable = is_indexed = is_partitioned = inside_type = format = data_size = None
if attributes_json:
pk = attributes_json[
'pk'] if 'pk' in attributes_json else None
delta = attributes_json[
'delta'] if 'delta' in attributes_json else None
is_nullable = attributes_json[
'nullable'] if 'nullable' in attributes_json else None
inside_type = attributes_json[
'type'] if 'type' in attributes_json else None
format = attributes_json[
'format'] if 'format' in attributes_json else None
flds[field_name] = {'type': type}
# String urn, Integer sortId, Integer parentSortId, String parentPath, String fieldName,
#String dataType, String isNullable, String defaultValue, Integer dataSize, String namespace, String description
sort_id += 1
field_detail_list.append([
"hive:///%s/%s" %
(one_db_info['database'], table['name']),
str(sort_id), '0', None, field_name, '', type,
data_size, None, None, is_nullable, is_indexed,
is_partitioned, default_value, None,
json.dumps(attributes_json)
])
elif TableInfo.field_list in table:
schema_json = {
'type': 'record',
'name': table['name'],
'fields': table[TableInfo.field_list]
} # construct a schema for data came from COLUMN_V2
for field in table[TableInfo.field_list]:
field_name = field['ColumnName']
type = field['TypeName']
# ColumnName, IntegerIndex, TypeName, Comment
flds[field_name] = {'type': type}
pk = delta = is_nullable = is_indexed = is_partitioned = inside_type = format = data_size = default_value = None # TODO ingest
field_detail_list.append([
"hive:///%s/%s" %
(one_db_info['database'], table['name']),
field['IntegerIndex'], '0', None, field_name, '',
field['TypeName'], None, None, None, is_nullable,
is_indexed, is_partitioned, default_value, None,
None
])
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_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()