I am trying to get data from a Bigquery table. In where clause i want to get the data on the basis of year like 2020. I am using EXTRACT(part FROM timestamp_expression [AT TIME ZONE timezone])
Query Looks like
with input as (Select created_at as timestamp_value,user_id from `seraphic-spider-311810.Demo.table2`)
SELECT
EXTRACT(Year FROM timestamp_value AT TIME ZONE "UTC") as year_value
FROM Input
where year_value like '2020%';
use WHERE EXTRACT(YEAR FROM timestamp_value) = 2020
Related
I would like to extract the date & hour from UTC time from the below table in bigquery. I have used timestamp for getting the date or time using the below code. I would like to apply the code for the entire column. How to apply timestamp for the entire column? Can you please assist with it?
SELECT EXTRACT(HOUR FROM TIMESTAMP "2020-05-03 16:49:47.583494")
My data is like this
I want result like this:
You can do it this way:
SELECT my_column AS original_value,
DATE_FORMAT(STR_TO_DATE(my_column, "%Y-%m-%d %H:%i:%s.%f UTC"), "%e/%m/%Y") AS date,
DATE_FORMAT(STR_TO_DATE(my_column, "%Y-%m-%d %H:%i:%s.%f UTC"), "%l%p") AS hour
FROM my_table;
I am assuming that the column is VARCHAR, that's why I am converting it to DATE.
Output:
Demo:
You can check the demo here.
Edit:
My initial thought was that OP wanted the query for MySQL (probably BigQuery is based on that). But it turns out that BigQuery is not based on MySQL. So you can use FORMAT_TIMESTAMP in BigQuery, this is how the query would look:
SELECT Occurrence AS original_value,
FORMAT_TIMESTAMP("%e/%m/%Y", Occurrence) AS date,
FORMAT_TIMESTAMP("%l%p", Occurrence) AS hour
FROM mytable
I have a table in BigQuery having a column Published_date with a datatype of "Timestamp". I want to calculate avg no of rows added per day (for a specific month) in that table. I have the following query
SELECT AVG(Num_Rows)
FROM (SELECT [Day]=DAY( Published_Date ), Num_Rows=COUNT(*)
FROM `mytable`
WHERE Published_Date BETWEEN '20190729' AND '20190729 '
GROUP BY DAY( Published_Date ) ) AS Z
But its generating the following error
Could not cast literal "20190729" to type TIMESTAMP
How should I deal with timestamp because I only need the date from timestamp column?
I want to calculate avg no of rows added per day (for a specific month) in that table
Below example for BigQuery Standard SQL
#standardSQL
SELECT AVG(Num_Rows) AS avg_rows_per_day
FROM (
SELECT DATE(Published_Date) AS day, COUNT(*) AS Num_Rows
FROM `project.dataset.mytable`
WHERE DATE(Published_Date) BETWEEN '2019-07-01' AND '2019-07-31'
GROUP BY day
)
Use explicit conversion:
WHERE Published_Date BETWEEN TIMESTAMP('2019-07-29') AND TIMESTAMP('2019-07-29')
Note that you have a column called "_date", but the error is saying that the value is a timestamp. I find this confusing. We use a convention of using _ts in columns that are timestamps (and _dt for datetime and _date for date).
Why is this important? The timestamp is UTC. So you might need to be careful about timezones and time components -- which is not obvious in a column called Publish_Date.
I'm using a SQL SELECT query to bring back all rows from a specific date.
The column I'm using is called TimeStamp (datetime)
(An example of data from this column = 01/02/2018 07:55:55)
What I would like is to return all rows from a specific date eg 24/06/2019
I have tried
SELECT top 20 TimeStamp
from Report
where TimeStamp = '02/01/2018 07:55:55'
which returns one row (which is correct as there is only one row containing this data)
If I then try
SELECT top 20 TimeStamp
from Report
where TimeStamp LIKE '02/01/2018%'
I get no results, I have also tried escaping the forward slashes
SELECT top 20 TimeStamp
from Report
where TimeStamp = '02\/01\/2018%'
Most databases support a string function called left(). If I assume that your "timestamp" is a string, then:
where left(timestamp, 10) = '01/02/2018'
However, it should be stored as a date or date/time. If so, then you can do:
where timestamp >= '2018-02-01' and
timestamp < '2018-02-02'
Note the use of standard formatted dates (YYYY-MM-DD). That is the way most databases implement date literals.
In SQL Server, you can also use:
where convert(date, timestamp) = '2018-02-01'
Both this and the previous version will use an index on timestamp, so both are reasonable solutions.
this should work
SELECT TimeStamp FROM report where convert(Date, TimeStamp) = '2019-06-24'
or select timestamp from report where timestamp between '2019-06-24' and '2019-06-25'. This will get you everything between 2019-06-24 00:00:00 and 2019-06-25 00:00:00 thus all records with date 2019-06-24
Convert timestamp value to date.
SELECT TimeStamp
FROM report
WHERE CAST(TimeStamp AS DATE) = '2019-06-24'
I am new to postgres and would appreciate any advice. I have postgres table with a timestamp column whose values are in the format: 1970-01-01 00:00:00
My objective is to select records from the last three whole months - December 2016, January 2017 and February 2017. How would one write this query with only read access using SELECT?
When I start with:
SELECT to_char("start_time", 'YYYY-MM-DD HH:MM:SS') FROM trips;
Times are converted to AM/PM but I am only interested in extracting and subsetting by month and year
Here you go:
SELECT *
FROM trips
WHERE start_time BETWEEN '2016-01-01 00:00:00'::timestamp AND '2017-02-28 23:59:59'::timestamp;
You can use extract or date_trunc function to extract month in postgresql.
Very similar to question get last three month records from table
For more details about date time functions in postgresql use below link.
https://www.postgresql.org/docs/9.1/static/functions-datetime.html
Here is one method:
select t.*
from t
where start_date >= date_trunc('month',now() - interval '3' month) and
start_date < date_trunc('month', now());
I am looking to use Teradata to group volume hourly over a date range when 'time' is a timestamp(6)
SELECT VOLUME, HOUR(time)
FROM table
GROUP BY HOUR(time)
There's no HOUR function in Teradata, according to Standard SQL it's EXTRACT:
EXTRACT(HOUR FROM timestampcol)
And of course you need a aggregate function, but i assume VOLUME will be the alias for a SUM/AVG/COUNT :-)