def _autocomplete(db, database=None, table=None, column=None, nested=None):
response = {}
try:
if database is None:
response['databases'] = db.get_databases()
elif table is None:
tables_meta = db.get_tables_meta(database=database)
response['tables_meta'] = tables_meta
elif column is None:
t = db.get_table(database, table)
response['hdfs_link'] = t.hdfs_link
response['columns'] = [column.name for column in t.cols]
response['extended_columns'] = massage_columns_for_json(t.cols)
response['partition_keys'] = [{'name': part.name, 'type': part.type} for part in t.partition_keys]
else:
col = db.get_column(database, table, column)
if col:
parse_tree = parser.parse_column(col.name, col.type, col.comment)
if nested:
parse_tree = _extract_nested_type(parse_tree, nested)
response = parse_tree
# If column or nested type is scalar/primitive, add sample of values
if parser.is_scalar_type(parse_tree['type']):
table_obj = db.get_table(database, table)
sample = db.get_sample(database, table_obj, column, nested)
if sample:
sample = set([row[0] for row in sample.rows()])
response['sample'] = sorted(list(sample))
else:
raise Exception('Could not find column `%s`.`%s`.`%s`' % (database, table, column))
except (QueryServerTimeoutException, TTransportException), e:
response['code'] = 503
response['error'] = e.message
def _autocomplete(db, database=None, table=None, column=None, nested=None):
response = {}
try:
if database is None:
response['databases'] = db.get_databases()
elif table is None:
response['tables'] = db.get_tables(database=database)
elif column is None:
t = db.get_table(database, table)
response['hdfs_link'] = t.hdfs_link
response['columns'] = [column.name for column in t.cols]
response['extended_columns'] = massage_columns_for_json(t.cols)
else:
col = db.get_column(database, table, column)
if col:
parse_tree = parser.parse_column(col.name, col.type, col.comment)
if nested:
parse_tree = _extract_nested_type(parse_tree, nested)
response = parse_tree
# If column or nested type is scalar/primitive, add sample of values
if parser.is_scalar_type(parse_tree['type']):
table_obj = db.get_table(database, table)
sample = db.get_sample(database, table_obj, column, nested)
if sample:
sample = set([row[0] for row in sample.rows()])
response['sample'] = sorted(list(sample))
else:
raise Exception('Could not find column `%s`.`%s`.`%s`' % (database, table, column))
except (QueryServerTimeoutException, TTransportException), e:
response['code'] = 503
response['error'] = e.message
def _autocomplete(db, database=None, table=None, column=None, nested=None):
response = {}
try:
if database is None:
response['databases'] = db.get_databases()
elif table is None:
tables_meta = db.get_tables_meta(database=database)
response['tables_meta'] = tables_meta
elif column is None:
table = db.get_table(database, table)
response['hdfs_link'] = table.hdfs_link
response['comment'] = table.comment
cols_extended = massage_columns_for_json(table.cols)
if 'org.apache.kudu.mapreduce.KuduTableOutputFormat' in str(
table.properties): # When queries from Impala directly
table.is_impala_only = True
if table.is_impala_only: # Expand Kudu columns information
query_server = get_query_server_config('impala')
db = dbms.get(db.client.user, query_server)
col_options = db.get_table_describe(database, table.name)
extra_col_options = dict([(col[0],
dict(zip(col_options.cols(), col)))
for col in col_options.rows()])
for col_props in cols_extended:
col_props.update(
extra_col_options.get(col_props['name'], {}))
response['support_updates'] = table.is_impala_only
response['columns'] = [column.name for column in table.cols]
response['extended_columns'] = cols_extended
response['is_view'] = table.is_view
response['partition_keys'] = [{
'name': part.name,
'type': part.type
} for part in table.partition_keys]
else:
col = db.get_column(database, table, column)
if col:
parse_tree = parser.parse_column(col.name, col.type,
col.comment)
if nested:
parse_tree = _extract_nested_type(parse_tree, nested)
response = parse_tree
# If column or nested type is scalar/primitive, add sample of values
if parser.is_scalar_type(parse_tree['type']):
sample = _get_sample_data(db, database, table, column)
if 'rows' in sample:
response['sample'] = sample['rows']
else:
raise Exception('Could not find column `%s`.`%s`.`%s`' %
(database, table, column))
except (QueryServerTimeoutException, TTransportException), e:
response['code'] = 503
response['error'] = e.message
def _autocomplete(db, database=None, table=None, column=None, nested=None, query=None, cluster=None):
response = {}
try:
if database is None:
response['databases'] = db.get_databases()
elif table is None:
tables_meta = db.get_tables_meta(database=database)
response['tables_meta'] = tables_meta
elif column is None:
if query is not None:
table = SubQueryTable(db, query)
else:
table = db.get_table(database, table)
response['hdfs_link'] = table.hdfs_link
response['comment'] = table.comment
cols_extended = massage_columns_for_json(table.cols)
if table.is_impala_only:
if db.client.query_server['server_name'] != 'impala': # Expand Kudu columns information
query_server = get_query_server_config('impala', cluster=cluster)
db = dbms.get(db.client.user, query_server, cluster=cluster)
col_options = db.get_table_describe(database, table.name)
extra_col_options = dict([(col[0], dict(list(zip(col_options.cols(), col)))) for col in col_options.rows()])
for col_props in cols_extended:
col_props.update(extra_col_options.get(col_props['name'], {}))
response['support_updates'] = table.is_impala_only
response['columns'] = [column.name for column in table.cols]
response['extended_columns'] = cols_extended
response['is_view'] = table.is_view
response['partition_keys'] = [{'name': part.name, 'type': part.type} for part in table.partition_keys]
else:
col = db.get_column(database, table, column)
if col:
parse_tree = parser.parse_column(col.name, col.type, col.comment)
if nested:
parse_tree = _extract_nested_type(parse_tree, nested)
response = parse_tree
# If column or nested type is scalar/primitive, add sample of values
if parser.is_scalar_type(parse_tree['type']):
sample = _get_sample_data(db, database, table, column, cluster=cluster)
if 'rows' in sample:
response['sample'] = sample['rows']
else:
raise Exception('Could not find column `%s`.`%s`.`%s`' % (database, table, column))
except (QueryServerTimeoutException, TTransportException) as e:
response['code'] = 503
response['error'] = e.message
except Exception as e:
LOG.warn('Autocomplete data fetching error: %s' % e)
response['code'] = 500
response['error'] = e.message
return response
def _autocomplete(db, database=None, table=None, column=None, nested=None, query=None, cluster=None):
response = {}
try:
if database is None:
response['databases'] = db.get_databases()
elif table is None:
tables_meta = db.get_tables_meta(database=database)
response['tables_meta'] = tables_meta
elif column is None:
if query is not None:
table = SubQueryTable(db, query)
else:
table = db.get_table(database, table)
response['hdfs_link'] = table.hdfs_link
response['comment'] = table.comment
cols_extended = massage_columns_for_json(table.cols)
if table.is_impala_only:
if db.client.query_server['server_name'] != 'impala': # Expand Kudu columns information
query_server = get_query_server_config('impala', cluster=cluster)
db = dbms.get(db.client.user, query_server, cluster=cluster)
col_options = db.get_table_describe(database, table.name)
extra_col_options = dict([(col[0], dict(zip(col_options.cols(), col))) for col in col_options.rows()])
for col_props in cols_extended:
col_props.update(extra_col_options.get(col_props['name'], {}))
response['support_updates'] = table.is_impala_only
response['columns'] = [column.name for column in table.cols]
response['extended_columns'] = cols_extended
response['is_view'] = table.is_view
response['partition_keys'] = [{'name': part.name, 'type': part.type} for part in table.partition_keys]
else:
col = db.get_column(database, table, column)
if col:
parse_tree = parser.parse_column(col.name, col.type, col.comment)
if nested:
parse_tree = _extract_nested_type(parse_tree, nested)
response = parse_tree
# If column or nested type is scalar/primitive, add sample of values
if parser.is_scalar_type(parse_tree['type']):
sample = _get_sample_data(db, database, table, column, cluster=cluster)
if 'rows' in sample:
response['sample'] = sample['rows']
else:
raise Exception('Could not find column `%s`.`%s`.`%s`' % (database, table, column))
except (QueryServerTimeoutException, TTransportException), e:
response['code'] = 503
response['error'] = e.message
def _autocomplete(db,
database=None,
table=None,
column=None,
nested=None,
query=None,
cluster=None,
operation='schema'):
response = {}
try:
if operation == 'functions':
response['functions'] = _get_functions(db, database)
elif operation == 'function':
response['function'] = _get_function(db, database)
elif database is None:
response['databases'] = db.get_databases()
elif table is None:
tables_meta = db.get_tables_meta(database=database)
response['tables_meta'] = tables_meta
elif column is None:
if query is not None:
table = SubQueryTable(db, query)
else:
table = db.get_table(database, table)
response['hdfs_link'] = table.hdfs_link
response['comment'] = table.comment
cols_extended = massage_columns_for_json(table.cols)
if table.is_impala_only: # Expand Kudu table information
if db.client.query_server['dialect'] != 'impala':
query_server = get_query_server_config('impala',
connector=cluster)
db = dbms.get(db.client.user,
query_server,
cluster=cluster)
col_options = db.get_table_describe(
database, table.name) # Expand columns information
extra_col_options = dict([
(col[0], dict(list(zip(col_options.cols(), col))))
for col in col_options.rows()
])
for col_props in cols_extended:
col_props.update(
extra_col_options.get(col_props['name'], {}))
primary_keys = [
col['name'] for col in extra_col_options.values()
if col.get('primary_key') == 'true'
] # Until IMPALA-8291
foreign_keys = [] # Not supported yet
else:
primary_keys = [pk.name for pk in table.primary_keys]
foreign_keys = table.foreign_keys
response['support_updates'] = table.is_impala_only
response['columns'] = [column.name for column in table.cols]
response['extended_columns'] = cols_extended
response['is_view'] = table.is_view
response['partition_keys'] = [{
'name': part.name,
'type': part.type
} for part in table.partition_keys]
response['primary_keys'] = [{'name': pk} for pk in primary_keys]
response['foreign_keys'] = [{
'name': fk.name,
'to': fk.type
} for fk in foreign_keys]
else:
col = db.get_column(database, table, column)
if col:
parse_tree = parser.parse_column(col.name, col.type,
col.comment)
if nested:
parse_tree = _extract_nested_type(parse_tree, nested)
response = parse_tree
# If column or nested type is scalar/primitive, add sample of values
if parser.is_scalar_type(parse_tree['type']):
sample = _get_sample_data(db,
database,
table,
column,
cluster=cluster)
if 'rows' in sample:
response['sample'] = sample['rows']
else:
raise Exception('Could not find column `%s`.`%s`.`%s`' %
(database, table, column))
except (QueryServerTimeoutException, TTransportException) as e:
response['code'] = 503
response['error'] = str(e)
except TypeError as e:
response['code'] = 500
response['error'] = str(e)
except Exception as e:
LOG.exception('Autocomplete data fetching error')
response['code'] = 500
response['error'] = str(e)
return response
