Below is the oracle SQL query,
that has to_date() function and adds with some days
select
to_date('01.01.1960','dd.MM.yyyy') + (1767097320000000/1000000/3600/24) as ACTUAL,
'2015-12-30 12:22:00' AS RESULT
from DUAL
Output
-----------------------------------------------
| ACTUAL | RESULT |
----------------------------------------------|
|2015-12-30 12:22:00 | 2015-12-30 12:22:00 |
-----------------------------------------------
My seek is to convert the above oracle query to_date('01.01.1960','dd.MM.yyyy') + (1767097320000000/1000000/3600/24) in spark SQL.
This looks the same with the given datetime format.
spark.sql("""
SELECT
from_unixtime(unix_timestamp('01.01.1960', "dd.MM.yyyy") + (1767097320000000/1000000), "yyyy-MM-dd HH:mm:ss") as RESULT,
'2015-12-30 12:22:00' as EXPECTED
""").show
+-------------------+-------------------+
| RESULT| EXPECTED|
+-------------------+-------------------+
|2015-12-30 12:22:00|2015-12-30 12:22:00|
+-------------------+-------------------+
SELECT
DATE_FORMAT(CAST(CAST(CAST(to_date('1960-01-01 00:00:00') AS TIMESTAMP) AS DOUBLE)+ (1767097320000000/1000000) AS TIMESTAMP), "yyyy-MM-dd HH:mm:ss") as RESULT
,'2015-12-30 12:22:00' as RESULT
from dual;
We have to convert the date string '1960-01-01 00:00:00' to timestamp object and then cast as double type.
Next, sum the milliseconds 1767097320000000/1000000 and the date as a double value.
The final value which is a double then cast as timestamp again
Another solution
date_format(CAST(unix_timestamp('1960-01-01 00:00:00')+ (1767097320000000/1000000) AS TIMESTAMP), "yyyy-MM-dd HH:mm:ss") as RESULT
Related
I'm trying to parse a timestamp which is in ISO Date 8601 format.
Example: 2021-04-10T14:11:00Z
This information is stored inside a JSON object and for that reason I'm extracting that data as a string:
The format I'm looking for is a yy-MM-dd hh:mm format and for that I've tried the following
SQL CODE
SELECT document_id,
json_extract(data, '$.Pair') as pair,
PARSE_TIMESTAMP('%y-%m-%d %H:%M', json_extract(data, '$.AlertTime')) as alerttime,
COUNT(document_id) as alert_count
FROM `tradingview-alerts-26eb8.alltables.TradingView_000_raw_latest` as alert_view
GROUP BY alerttime, document_id, pair
Errors
The code from above causes the following error:
Failed to parse input string '"2021-04-10T03:17:00Z"
The reason for this is the T in the middle of the date, I believe,
In order to discard that I tried this change:
SUBSTR(json_extract(data, '$.AlertTime'), 1, 10))
But with that I'm getting an error on a different row:
Failed to parse input string '"2021-04-1'
I'm wondering if it is because of how the date is being presented (year-month-date) the date not having 2 digits? such as 2021-04-01 instead of 2021-04-1.
However if I try with
SUBSTR(json_extract(data, '$.AlertTime'), 1, 11))
The error I'm getting is
Failed to parse input string '"2021-04-10'
You need to include those ISO symbols into format specifier as constants:
select parse_timestamp('%FT%TZ', '2021-04-12T17:38:10Z')
| f0_ |
---------------------------
| 2021-04-12 17:38:10 UTC |
UPD: If you have fractional seconds, you can include optional milliseconds element %E*S instead of time element %T. For non-UTC timestamps there should also be timezone element: %Ez. So, the possible solution could be:
with a as (
select '2021-04-12T20:44:06.95841Z' as ts_str union all
select '2021-04-12T23:44:07.83738+03:00' union all
select '2021-04-12T23:44:08+03:00'
)
select parse_timestamp('%FT%H:%M:%E*S%Ez', regexp_replace(ts_str, 'Z$', '+00:00')) as ts
from a
| ts |
|--------------------------------|
| 2021-04-12 20:44:06.958410 UTC |
| 2021-04-12 20:44:07.837380 UTC |
| 2021-04-12 20:44:08 UTC |
I think you can use timestamp => datetime func.
Like this
datetime(timestamp(2021-11-29T00:00:00.000Z))
I have to select the value 2019-03-25 from a date column of a table but in the following format:
2019-03-25T00:00:00.000+02:00
Hon can I get it?
Oracle 10g
Thanks!
The date datatype does not store milliseconds and timezone information, so I undertand your question as how to format a date to the target forma, with fixed values for milliseconds and timezone.
If so, you can use to_char() like so:
to_char(mycol, 'yyyy-mm-dd"T"hh24:mi:ss".000+2:00"')
You can CAST your DATE to a TIMESTAMP and then use FROM_TZ to set the time zone and then format it to your requirements using TO_CHAR:
SELECT TO_CHAR(
FROM_TZ( CAST( your_date AS TIMESTAMP ), '+02:00' ),
'YYYY-MM-DD"T"HH24:MI:SS.FF3TZH:TZM'
) AS formatted_date
FROM your_table;
Which, for your sample data:
CREATE TABLE your_table ( your_date ) AS
SELECT DATE '2019-03-25' FROM DUAL
Outputs:
| FORMATTED_DATE |
| :---------------------------- |
| 2019-03-25T00:00:00.000+02:00 |
db<>fiddle here
We can not store timezone information in db that's why we can simply use below format,
select to_char(sysdate,'YYYY-MM-DD')||'T'||to_char(sysdate,'HH24:MI:SS') from dual
I have a column in Athena with Timestamp Data Type and format is: 2019-08-28 00:00:00.000
How to format it to Date format using SQL to be:
DD-MON-YYYY
Thanks.
WITH test AS (
SELECT '2019-08-28 00:00:00.000' AS str
)
SELECT format_datetime(cast(str AS timestamp), 'dd-MM-YYYY')
FROM test
Result:
_col0
1 28-08-2019
I have a column updated_at that returns an array
["2019-01-05T17:28:32.506-05:00","2019-06-15T13:22:02.625-04:00"]
But I want the output date format like this 2019-01-03.
How can I accomplish this in sql databricks?
Thanks!
Try unnest and cast that as a date:
with ts_array as
(select array['2019-01-05T17:28:32.506-05:00','2019-06-15T13:22:02.625-04:00'] as tsa)
select unnest(tsa)::date from ts_array ;
You can use "date_trunc" SQL function to get the output in date format.
date_trunc(fmt, ts) - Returns timestamp ts truncated to the unit specified by the format model fmt. fmt should be one of [“YEAR”, “YYYY”, “YY”, “MON”, “MONTH”, “MM”, “DAY”, “DD”, “HOUR”, “MINUTE”, “SECOND”, “WEEK”, “QUARTER”]
Examples:
> SELECT date_trunc('YEAR', '2015-03-05T09:32:05.359');
2015-01-01 00:00:00
> SELECT date_trunc('MM', '2015-03-05T09:32:05.359');
2015-03-01 00:00:00
> SELECT date_trunc('DD', '2015-03-05T09:32:05.359');
2015-03-05 00:00:00
> SELECT date_trunc('HOUR', '2015-03-05T09:32:05.359');
2015-03-05 09:00:00
Reference: Databricks - SQL Functions.
Hope this helps.
I have a table with a VARCHAR(64) column called datetimestamp that contains datetime strings with the following format:
[02/Jun/2016:23:58:30 +0000].
I'm trying to convert this to a date using to_date(datetimestamp, 'DD/Mon/YYYY:HH24:MM:SS') in my select statement, but I'm getting an 'Invalid Format' error. Not sure if its the UTC bit or what that's messing it up... what's the proper syntax?
Thanks!
It is a bit complicated since to_timestamp does not allow time zone information.
I have come up with this query:
WITH d(part) AS
(SELECT regexp_matches(
'02/Jun/2016:23:58:30 +0000',
'^([^ ]*) ([-+]?\d\d)(\d\d)$'
)
)
SELECT
CAST (to_timestamp(d.part[1], 'DD/Mon/YYYY:HH24:MI:SS')
AT TIME ZONE (d.part[2] || ':' || d.part[3])
AS timestamp with time zone)
AS converted
FROM d;
converted
------------------------
2016-06-02 21:58:30+02
(1 row)
(I am at time zone UTC+02.)
select to_date('02/Jun/2016:23:58:30 +0000', 'DD/Mon/YYYY:HH24:MI:SS');
| to_date |
|------------|
| 2016-06-02 |