I have this table
I want to create a query that will return data in the following format:
date (just a day), sms_number, etc...
So I want to unite rows from the 1st table by days and return statistics for it, for example amount of sms (rows) for one day (for example for 2020-07-07, time should not be taken into account).
How do I do this using SQL (provide an example)?
Try the following:
select DATE_FORMAT(date_,'%Y-%m-%d') AS
date_, count(date_) as sms_number from
sms_logs
group by DATE_FORMAT(date_,'%Y-%m-%d')
order by date_ DESC
See a MySQL demo from db-fiddle.
Related
I can't seem to find a perhaps easy solution to what I'm trying to accomplish here, using SQL and, more importantly, QuestDB. I also find it hard to put my exact question into words so bear with me.
Input
My real input is different of course but a similar dataset or case is the gas_prices table on the demo page of QuestDB. On https://demo.questdb.io, you can directly write and run queries against some sample database, so it should be easy enough to follow.
The main task I want to accomplish is to find out which month was responsible for the year's highest galon price.
Output
Using the following query, I can get the average galon price per month just fine.
SELECT timestamp, avg(galon_price) as avg_per_month FROM 'gas_prices' SAMPLE BY 1M
timestamp
avg_per_month
2000-06-05T00:00:00.000000Z
1.6724
2000-07-05T00:00:00.000000Z
1.69275
2000-08-05T00:00:00.000000Z
1.635
...
...
Then, I get all these monthly averages, group them by year and return the maximum galon price per year by wrapping the above query in a subquery, like so:
SELECT timestamp, max(avg_per_month) as max_per_year FROM (
SELECT timestamp, avg(galon_price) as avg_per_month FROM 'gas_prices' SAMPLE BY 1M
) SAMPLE BY 12M
timestamp
max_per_year
2000-01-05T00:00:00.000000Z
1.69275
2001-01-05T00:00:00.000000Z
1.767399999999
2002-01-05T00:00:00.000000Z
1.52075
...
...
Wanted output
I want to know which month was responsible for the maximum price of a year.
Looking at the output of the above query, we see that the maximum galon price for the year 2000 was 1.69275. Which month of the year 2000 had this amount as average price? I'd like to display this month in an additional column.
For the first row, July 2000 is shown in the additional column for year 2000 because it is responsible for the highest average price in 2000. For the second row, it was May 2001 as that month had the highest average price of 2001.
timestamp
max_per_year
which_month_is_responsible
2000-01-05T00:00:00.000000Z
1.69275
2000-07-05T00:00:00.000000Z
2001-01-05T00:00:00.000000Z
1.767399999999
2001-05-05T00:00:00.000000Z
...
...
What did I try?
I tried by adding a subquery to the SELECT to have a "duplicate" of some sort for the timestamp column but that's apparently never valid in QuestDB (?), so probably the solution is by adding even more subqueries in the FROM? Or a UNION?
Who can help me out with this? The data is there in the database and it can be calculated. It's just a matter of getting it out.
I think 'wanted output' can be achieved with window functions.
Please have a look at:
CREATE TABLE electricity (ts TIMESTAMP, consumption DOUBLE) TIMESTAMP(ts);
INSERT INTO electricity
SELECT (x*1000000)::timestamp, rnd_double()
FROM long_sequence(10000000);
SELECT day, ts, max_per_day
FROM
(
SELECT timestamp_floor('d', ts) as day,
ts,
avg_in_15_min as max_per_day,
row_number() OVER (PARTITION BY timestamp_floor('d', ts) ORDER BY avg_in_15_min desc) as rn_per_day
FROM
(
SELECT ts, avg(consumption) as avg_in_15_min
FROM electricity
SAMPLE BY 15m
)
) WHERE rn_per_day = 1
I am asking for help with this item. I am a novice to SQL and not very sure how to handle this problem I appreciate any help from the forum.
I have a table that is updated multiple times a day. I would like to create a view that only displays the last update that was made for a given day.
Here is a sample of the data
enter image description here
This is the desired result of the SQL Query when the data set provided has been queries
enter image description here
As I understood you want to get the last record of every day.
Just group it by day
You will have to use EXTRACT to do it
Example: EXTRACT(DAY FROM DATE)
Then select the max time from the column where you have the time of the day. If you dont have the time in a different column you will also need to extract it.
SELECT MAX(TIME_COLUMN) FROM `TABLE_NAME`
GROUP BY EXTRACT(DAY FROM DATE)
SELECT MAX (your_date) AS "Max Date"
FROM your_table
I am querying a table that has the date column as follows:
date
2021-03-08 05:05:31+00
2021-03-08 05:10:31+00
How can I select all the rows that contain 05:05 as the hour and minute in SQL? i.e. rows where hour = 05, and minute = 05. In this case it will be the first row.
Q: How can I select all the rows that contain 05:05 as the hour and minute in SQL?
A: For MySQL, look in the MySql Date and Time functions. There, you'll find Extract().
You can use it as follows:
https://www.w3schools.com/sql/func_mysql_extract.asp
Extract the minute from a datetime:
SELECT EXTRACT(MINUTE FROM "2017-06-15 09:34:21");
This assumes that you're storing the column as a "Date" type.
Different RDBMS vendors have different Date/Time functions. You'll have to read the documentation and experiment to determine which syntax to use for your particular DB vendor and your particular table schema.
You Can Use below Query for get Result as per your question .
There is DateName function in SQL and you can put this in your query as below.
CreatedDate is column name..
Example :
Select * from #tmp1 where datename(hour,createdDate)=07 And datename(minute,CreatedDate)=07
I'm looking to only select one data point from each date in my report. I want to ensure each day is accounted for and has at least one row of information, as we had to do a few different things to move a large data file into our data warehouse (import one large Google Sheet for some data, use Python for daily pulls of some of the other data - want to make sure no date was left out), and this data goes from now through last summer. I could do a COUNT DISTINCT clause to just make sure the number of days between the first data point and yesterday (the latest data point), but I want to verify each day is accounted for. Should mention I am in BigQuery. Also, an example of the created_at style is: 2021-02-09 17:05:44.583 UTC
This is what I have so far:
SELECT FIRST(created_at)
FROM 'large_table'
ORDER BY created_at
**I know FIRST is probably not the best clause for this case, and it's currently acting to grab the very first data point in created_at, but just as a jumping-off point.
You can use aggregation:
select any_value(lt).*
from large_table lt
group by created_at
order by min(created_at);
Note: This assumes that created_at is a date -- or at least only has one value per date. You might need to convert it to a date:
select any_value(lt).*
from large_table lt
group by date(created_at)
order by min(created_at);
BigQuery equivalent of the query in your question
SELECT created_at
FROM 'large_table'
ORDER BY created_at
LIMIT 1
I have a table named Sales and a column within it named Date. I'm simply trying to find how many sales were made on a specific date. My intuition was to use something like this:
SELECT COUNT(Date) FROM Sales WHERE Date='2015-04-04'
this should count all sales that were made on that date, but that returns 0. What am I doing wrong?
While it is difficult to be precise without table definitions or an indication of what RDBMS you are using, it is likely that Date is a time/date stamp, and that the result you want would be obtained either by looking for a range from the beginning of the day to the end of the day in your WHERE clause, or by truncating Date down to a date without the time before comparing it to a date.
Try the below once.
select count(*) from <t.n> where date like '2015-04-04%';
When you want to find the count of rows based on a field (Date) You need to Group By over it like this:
SELECT Date, COUNT(*)
FROM Sales
GROUP BY Date
Now you have all count of rows for each Date.
Type and Value of Date is important in the result of the above query.
For example in SQL Server your best try is to convert a DateTime field to varchar and then check it as the result of CONVERT like this:
SELECT COUNT(*)
FROM Sales
WHERE CONVERT(VARCHAR, Date, 111) = '2015/04/04'