crazyscientist edited a comment on issue #8943:
URL:
https://github.com/apache/incubator-superset/issues/8943#issuecomment-635170230
I can confirm that this issue is not specific to WSL. I used this setup and
end up with the same exception:
- Ubuntu 18.04
- PostgreSQL from repos
- Database was created and populated by a Django app
- superset's devel server is running in a venv with Python 3.6
In the SQL Lab queries are executed and results are shown, When I proceed to
the data exploration mode and rerun the query the traceback looks like this:
```
INFO:superset.connectors.sqla.models:SELECT DATE_TRUNC('week', end_date) AS
__timestamp, count(*) AS count
FROM (SELECT
r.request_id,
r.created,
r.end_date,
s.name
FROM smeltapp_request r
JOIN smeltapp_status s
ON r.status_id = s.id
WHERE
r.kind = 'RR'
AND
r.end_date is not NULL
ORDER BY end_date
LIMIT 1000) AS expr_qry GROUP BY DATE_TRUNC('week', end_date) ORDER BY count
DESC
LIMIT 50000
Tz-aware datetime.datetime cannot be converted to datetime64 unless utc=True
Traceback (most recent call last):
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/pandas/core/arrays/datetimes.py",
line 1979, in objects_to_datetime64ns
values, tz_parsed = conversion.datetime_to_datetime64(data)
File "pandas/_libs/tslibs/conversion.pyx", line 185, in
pandas._libs.tslibs.conversion.datetime_to_datetime64
ValueError: Array must be all same time zone
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/superset/viz.py",
line 443, in get_df_payload
df = self.get_df(query_obj)
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/superset/viz.py",
line 264, in get_df
df[DTTM_ALIAS], utc=False, format=timestamp_format
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/pandas/util/_decorators.py",
line 208, in wrapper
return func(*args, **kwargs)
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/pandas/core/tools/datetimes.py",
line 778, in to_datetime
values = convert_listlike(arg._values, True, format)
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/pandas/core/tools/datetimes.py",
line 463, in _convert_listlike_datetimes
allow_object=True,
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/pandas/core/arrays/datetimes.py",
line 1984, in objects_to_datetime64ns
raise e
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/pandas/core/arrays/datetimes.py",
line 1975, in objects_to_datetime64ns
require_iso8601=require_iso8601,
File "pandas/_libs/tslib.pyx", line 465, in
pandas._libs.tslib.array_to_datetime
File "pandas/_libs/tslib.pyx", line 543, in
pandas._libs.tslib.array_to_datetime
ValueError: Tz-aware datetime.datetime cannot be converted to datetime64
unless utc=True
ERROR:superset.viz:Tz-aware datetime.datetime cannot be converted to
datetime64 unless utc=True
Traceback (most recent call last):
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/pandas/core/arrays/datetimes.py",
line 1979, in objects_to_datetime64ns
values, tz_parsed = conversion.datetime_to_datetime64(data)
File "pandas/_libs/tslibs/conversion.pyx", line 185, in
pandas._libs.tslibs.conversion.datetime_to_datetime64
ValueError: Array must be all same time zone
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/superset/viz.py",
line 443, in get_df_payload
df = self.get_df(query_obj)
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/superset/viz.py",
line 264, in get_df
df[DTTM_ALIAS], utc=False, format=timestamp_format
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/pandas/util/_decorators.py",
line 208, in wrapper
return func(*args, **kwargs)
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/pandas/core/tools/datetimes.py",
line 778, in to_datetime
values = convert_listlike(arg._values, True, format)
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/pandas/core/tools/datetimes.py",
line 463, in _convert_listlike_datetimes
allow_object=True,
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/pandas/core/arrays/datetimes.py",
line 1984, in objects_to_datetime64ns
raise e
File
"/home/andi/virtualenvs/superset/lib/python3.6/site-packages/pandas/core/arrays/datetimes.py",
line 1975, in objects_to_datetime64ns
require_iso8601=require_iso8601,
File "pandas/_libs/tslib.pyx", line 465, in
pandas._libs.tslib.array_to_datetime
File "pandas/_libs/tslib.pyx", line 543, in
pandas._libs.tslib.array_to_datetime
ValueError: Tz-aware datetime.datetime cannot be converted to datetime64
unless utc=True
```
Looking at the raw data in the database I noticed that all timestamps have
in fact the same timezone, but daylight saving is encoded in the timezone. So I
have two groups of entries. For one group `extract(timezone from r.created)`
returns 3600; for the other it returns 7200.
Also please notice, that I did not use a time range filter and still get
this error.
---
In case the table definitions are of interest (I have excluded constraints
and indizes):
```sql
CREATE TABLE public.smeltapp_request
(
id integer NOT NULL DEFAULT nextval('smeltapp_request_id_seq'::regclass),
created timestamp with time zone NOT NULL,
request_id integer NOT NULL,
kind character varying(2) NOT NULL,
status_id integer,
end_date timestamp with time zone
);
CREATE TABLE public.smeltapp_status
(
id integer NOT NULL DEFAULT nextval('smeltapp_status_id_seq'::regclass),
name character varying(200) NOT NULL
);
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