def _fetch(self, cursor):
rows = cursor.fetchall()
# TODO(wesm): please evaluate/reimpl to optimize for perf/memory
dtypes = [self._db_type_to_dtype(x[1]) for x in cursor.description]
names = [x[0] for x in cursor.description]
cols = {}
for (col, name, dtype) in czip(czip(*rows), names, dtypes):
try:
cols[name] = pd.Series(col, dtype=dtype)
except TypeError:
# coercing to specified dtype failed, e.g. NULL vals in int col
cols[name] = pd.Series(col)
return pd.DataFrame(cols, columns=names)
def _fetch(self, cursor):
data, columns = cursor
names, types = czip(*columns)
cols = {}
for (col, name, db_type) in czip(data, names, types):
dtype = self._db_type_to_dtype(db_type, name)
try:
cols[name] = pd.Series(col, dtype=dtype)
except TypeError:
cols[name] = pd.Series(col)
return pd.DataFrame(cols, columns=names)
def _fetch(self, cursor):
import pandas as pd
rows = cursor.fetchall()
# TODO(wesm): please evaluate/reimpl to optimize for perf/memory
dtypes = [self._db_type_to_dtype(x[1]) for x in cursor.description]
names = [x[0] for x in cursor.description]
cols = {}
for (col, name, dtype) in czip(czip(*rows), names, dtypes):
try:
cols[name] = pd.Series(col, dtype=dtype)
except TypeError:
# coercing to specified dtype failed, e.g. NULL vals in int col
cols[name] = pd.Series(col)
return pd.DataFrame(cols, columns=names)
def _execute(self, query, external_tables=(), results=True):
if isinstance(query, DDL):
query = query.compile()
self.log(query)
response = self.con.process_ordinary_query(
query,
columnar=True,
with_column_types=True,
external_tables=external_tables)
if not results:
return response
data, columns = response
colnames, typenames = czip(*columns)
coltypes = list(map(ClickhouseDataType.parse, typenames))
return data, colnames, coltypes
