Redshift - Finding difference between rows for the same id - amazon-redshift

I am trying to find the difference in value across rows and have built the below
Data:
cust_id,sales
cust_1,30
cust_1,43
cust_1,4
cust_2,5
cust_2,8
I have built the below:
select cust_id,sales, sales - lag(sales) over (order by cust_id) as change from table;
This returns the below output:
cust_id,sales, difference
cust_1,30,13
cust_1,43,-39
cust_1,4,1
cust_2,5,3
cust_2,8,
How do I change the above output to only calculate difference if the cust_id is same and leave it blank if the cust_id changes. Using Redshift.

Related

How to get latest data for a column when using grouping in postgres

I am using postgres alongside sequelize. I have encountered a case where I need to write a coustom query which groups the records are a particular field. I know for the remaning columns that are not used for grouping, I need to use a aggregate function like SUM. But the problem is that for some columns I need to get the one what is the latest one (DESC sorted by created_at). I see no function in sql to do so. Is my only option to write subqueries or is there a better way? Thanks?
For better understanding, If you look at the below picture, I want the group the records with address. So after the query there should only be two records, one with sydney and the other with new york. But when it comes to the distance, I want the result of the query to contain the distance form the row that was most recently created, i.e with the latest created_at.
so the final two query results should be:
sydney 100 2022-09-05 18:14:53.492131+05:45
new york 40 2022-09-05 18:14:46.23328+05:45
select address, distance, created_at
from(
select address, distance, created_at, row_number() over(partition by address order by created_at DESC) as rn
from table) x
where rn = 1

Postgres: Storing output of moving average query to a column

I have a table in Postgres 14.2
Table name is test
There are 3 columns: date, high, and five_day_mavg (date is PK if it matters)
I have a select statement which properly calculates a 5 day moving average based on the data in high.
select date,
avg(high) over (order by date rows between 4 preceding and current row) as mavg_calc
from test
It products output as such:
I have 2 goals:
First to store the output of the query in five_day_mavg.
Second to store this in such a way that when I a new row with data
in high, it automatically calculates that value
The closest I got was:
update test set five_day_mavg = a.mav_calc
from (
select date,
avg(high) over (order by date rows between 4 preceding and current row) as mav_calc
from test
) a;
but all that does is sets the value of every row in five_day_mavg to entire average of high
Thanks to #a_horse_with_no_name
I played around with the WHERE clause
update test l set five_day_mavg = b.five_day_mavg from (select date, avg(high) over (order by date rows between 4 preceding and current row) as five_day_mavg from test )b where l.date = b.date;
a couple of things. I defined each table. The original table I aliased as l, the temporary table created by doing a windows function (the select statement in parenthesis) I aliased as b and I joined with the WHERE clause on date which is the index/primary key.
Also, I was using 'a' as the letter for alias, and I think that may have contributed to the issue.
Either way, solved now.

Divide count of Table 1 by count of Table 2 on the same time interval in Tableau

I have two tables with IDs and time stamps. Table 1 has two columns: ID and created_at. Table 2 has two columns: ID and post_date. I'd like to create a chart in Tableau that displays the Number of Records in Table 1 divided by Number of Records in Table 2, by week. How can I achieve this?
One way might be to use Custom SQL like this to create a new data source for your visualization:
SELECT created_table.created_date,
created_table.created_count,
posted_table.posted_count
FROM (SELECT TRUNC (created_at) AS created_date, COUNT (*) AS created_count
FROM Table1) created_table
LEFT JOIN
(SELECT TRUNC (post_date) AS posted_date, COUNT (*) AS posted_count
FROM Table2) posted_table
ON created_table.created_date = posted_table.posted_date
This would give you dates and counts from both tables for those dates, which you could group using Tableau's date functions in the visualization. I made created_table the first part of the left join on the assumption that some records would be created and not posted, but you wouldn't have posts without creations. If that isn't the case you will want a different join.

Calculate Mode - "Highest frequency row" DB2

What would be the most efficient way to calculating the mode across tables with joins in DB2..
I am trying to get the value with the most frequency(count) for a given column(ID - candidate key for joined table) on a given date.
The idea is to get the most common (value) from the table which has different (value)s for some accounts (for the same ID and date). We need to make it unique for use in another table.
You can use common table expressions [CTE's], indicated by WITH, to break the logic down into logical steps. First we'll build the summary rows, then we'll assign a ranking to the rows within each group, then pick out the ones that with the highest count of records.
Let's say we want to know which flavor of each item sells the most frequently on each date (perhaps assuming a record is quantity one).
WITH s as
(
SELECT itemID, saleDate, flavor, count(*) as tally
FROM sales
GROUP BY itemID, saleDate, flavor
), r as
(
SELECT itemID, saleDate, flavor, tally,
RANK() OVER (PARTITION BY itemID, saleDate ORDER BY tally desc) as pri
FROM s
)
SELECT itemID, saleDate, flavor, tally
FROM r
WHERE pri = 1
Here the names "s" and "r" refer to the result set from their respective CTE's. These names can then be used as to represent a table in another part of the statement.
The pri column will have the RANK() of tally value on the summary row from the first section "s" within the window of itemID and saleDate. Tally is descending, because we want the largest value first, which will get a RANK() of 1. Then in the main SELECT we simply pick those summary records which were first in their partition.
By using RANK() or DENSE_RANK() we could get back multiple flavors for an itemID, saleDate, if they are tied for first place. This could be eliminated by replacing RANK() with ROW_NUMBER(), but it would arbitrarily pick one of the tied flavors as a winner, and this may not be correct answer for the problem at hand.
If we had a sales quantity column in the table, we could replace COUNT(*) with SUM(salesqty) and find what had sold the most units.

Equivalent of LIMIT for DB2

How do you do LIMIT in DB2 for iSeries?
I have a table with more than 50,000 records and I want to return records 0 to 10,000, and records 10,000 to 20,000.
I know in SQL you write LIMIT 0,10000 at the end of the query for 0 to 10,000 and LIMIT 10000,10000 at the end of the query for 10000 to 20,000
So, how is this done in DB2? Whats the code and syntax?
(full query example is appreciated)
Using FETCH FIRST [n] ROWS ONLY:
http://publib.boulder.ibm.com/infocenter/dzichelp/v2r2/index.jsp?topic=/com.ibm.db29.doc.perf/db2z_fetchfirstnrows.htm
SELECT LASTNAME, FIRSTNAME, EMPNO, SALARY
FROM EMP
ORDER BY SALARY DESC
FETCH FIRST 20 ROWS ONLY;
To get ranges, you'd have to use ROW_NUMBER() (since v5r4) and use that within the WHERE clause: (stolen from here: http://www.justskins.com/forums/db2-select-how-to-123209.html)
SELECT code, name, address
FROM (
SELECT row_number() OVER ( ORDER BY code ) AS rid, code, name, address
FROM contacts
WHERE name LIKE '%Bob%'
) AS t
WHERE t.rid BETWEEN 20 AND 25;
Developed this method:
You NEED a table that has an unique value that can be ordered.
If you want rows 10,000 to 25,000 and your Table has 40,000 rows, first you need to get the starting point and total rows:
int start = 40000 - 10000;
int total = 25000 - 10000;
And then pass these by code to the query:
SELECT * FROM
(SELECT * FROM schema.mytable
ORDER BY userId DESC fetch first {start} rows only ) AS mini
ORDER BY mini.userId ASC fetch first {total} rows only
Support for OFFSET and LIMIT was recently added to DB2 for i 7.1 and 7.2. You need the following DB PTF group levels to get this support:
SF99702 level 9 for IBM i 7.2
SF99701 level 38 for IBM i 7.1
See here for more information: OFFSET and LIMIT documentation, DB2 for i Enhancement Wiki
Here's the solution I came up with:
select FIELD from TABLE where FIELD > LASTVAL order by FIELD fetch first N rows only;
By initializing LASTVAL to 0 (or '' for a text field), then setting it to the last value in the most recent set of records, this will step through the table in chunks of N records.
#elcool's solution is a smart idea, but you need to know total number of rows (which can even change while you are executing the query!). So I propose a modified version, which unfortunately needs 3 subqueries instead of 2:
select * from (
select * from (
select * from MYLIB.MYTABLE
order by MYID asc
fetch first {last} rows only
) I
order by MYID desc
fetch first {length} rows only
) II
order by MYID asc
where {last} should be replaced with row number of the last record I need and {length} should be replaced with the number of rows I need, calculated as last row - first row + 1.
E.g. if I want rows from 10 to 25 (totally 16 rows), {last} will be 25 and {length} will be 25-10+1=16.
Try this
SELECT * FROM
(
SELECT T.*, ROW_NUMBER() OVER() R FROM TABLE T
)
WHERE R BETWEEN 10000 AND 20000
The LIMIT clause allows you to limit the number of rows returned by the query. The LIMIT clause is an extension of the SELECT statement that has the following syntax:
SELECT select_list
FROM table_name
ORDER BY sort_expression
LIMIT n [OFFSET m];
In this syntax:
n is the number of rows to be returned.
m is the number of rows to skip before returning the n rows.
Another shorter version of LIMIT clause is as follows:
LIMIT m, n;
This syntax means skipping m rows and returning the next n rows from the result set.
A table may store rows in an unspecified order. If you don’t use the ORDER BY clause with the LIMIT clause, the returned rows are also unspecified. Therefore, it is a good practice to always use the ORDER BY clause with the LIMIT clause.
See Db2 LIMIT for more details.
You should also consider the OPTIMIZE FOR n ROWS clause. More details on all of this in the DB2 LUW documentation in the Guidelines for restricting SELECT statements topic:
The OPTIMIZE FOR clause declares the intent to retrieve only a subset of the result or to give priority to retrieving only the first few rows. The optimizer can then choose access plans that minimize the response time for retrieving the first few rows.
There are 2 solutions to paginate efficiently on a DB2 table :
1 - the technique using the function row_number() and the clause OVER which has been presented on another post ("SELECT row_number() OVER ( ORDER BY ... )"). On some big tables, I noticed sometimes a degradation of performances.
2 - the technique using a scrollable cursor. The implementation depends of the language used. That technique seems more robust on big tables.
I presented the 2 techniques implemented in PHP during a seminar next year. The slide is available on this link :
http://gregphplab.com/serendipity/uploads/slides/DB2_PHP_Best_practices.pdf
Sorry but this document is only in french.
Theres these available options:-
DB2 has several strategies to cope with this problem.
You can use the "scrollable cursor" in feature.
In this case you can open a cursor and, instead of re-issuing a query you can FETCH forward and backward.
This works great if your application can hold state since it doesn't require DB2 to rerun the query every time.
You can use the ROW_NUMBER() OLAP function to number rows and then return the subset you want.
This is ANSI SQL
You can use the ROWNUM pseudo columns which does the same as ROW_NUMBER() but is suitable if you have Oracle skills.
You can use LIMIT and OFFSET if you are more leaning to a mySQL or PostgreSQL dialect.