I have a large table - around 2B records. I added a column to the table and am running a simple update query to set the value of my new column to a single value for all rows. The DBA said my query is 90+ skewed and I need to optimize the query. Anyone have suggestions on how to do that? I am new to working with very large data sets so any advice would be helpful.
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I am trying to Update a huge table in Teradata on a daily basis. The Update Statement is taking a lot of AMPCPUTime.
Table contains 65 Billion rows and 100-200 Million Rows are updated.
Table is a Set Table with Non Unique PI. The data distribution is quite even with 0.8 Skew Factor.
What is the way to reduce the AMPCPU Time?
The Update is done using a Stage table. Join is on a subset of PI columns.
Attempts: Changed the PI of stage table same as Target Table. Explain PLan says a Merge Update is being performed. But AMPCPUTime is rather increasing.
Tried Delete and Insert but Delete and Insert also taking greater AMPCPUTime.
Im a trainee working with databases.
Im working on PowerBI report based on SQL query where all of the needed joins are included for my data to be obtained. So Im working within one dataset.
I have made a table where I can show number of transaction(like invoice number) and name of person that made that transaction. My problem lies in creating a measure that will influence that table. It should work like a having clausule from SQL (well at least my boss said that).
I would like for this measure to force this table to show only data for people that have made more than 2 transactions (they have more than 2 invoice numbers [so there are more than two rows for this person]) .
I tried to do it by writing a measure like that:
Measure = COUNTAX(
Query1;counta([Salesman])>2)
Or like that:
Measure 2 =
FILTER( Query1; counta(Query1[Salesman])>2 )
But i only got a bar graph that is showing me how many transactions were made by each person. When Im adding this measure to this table i see that for each row i got value 1.
Im new to the PowerBi and DAX so it's quite a big hurdle for me. Can someone share his/hers knowledge to help solve this problem? I would be much obliged.
I found a solution for my problem.
I created a second query that counted transactions for each person with their names. I created relationship between my two queries. Next I added counting attribute to my table with data from query one and I used filter on my counting attribute. After that this attribute can be just hidden and It works perfectly.
On top of that I created a measure and made a chart using this measure. It looks nice and clear.
The measure looks like that:
Measure =
COUNTAX(
Query1;counta([Salesman])
)
I filtered this measure too to get wanted result.
I have to prepare a table where I will keep weekly results for some aggregated data. Table will have 30 fields (10 CHARACTERs, 20 DECIMALs), I think I will have 250k rows weekly.
In my head I can see two scenarios:
Set table and relying on teradata in preventing duplicate rows - it should skip duplicate entries while inserting new data
Multi set table with UPI - it will give an error upon inserting duplicate row.
INSERT statement is going to be executed through VBA on excel, where handling possible teradata errors is not a problem.
Which scenario will be faster to run in a year time where there will be circa 14 millions rows
Is there any other way to have it done?
Regards
On a high level, since you would be having a comparatively high data count on your table, it is advisable not to use SET tables, rather go with the multiset table.
For more info you can refer to this link
http://www.dwhpro.com/teradata-multiset-tables/
Why do you care about Duplicate Rows? When you store weekly aggregates there should be no duplicates at all. And Duplicate Rows are not the same as duplicate Primary Key values.
Simply choose a PI which fits best your join/access pattern (maybe partition by date). To avoid any potential duplicates you might simply use MERGE instead of INSERT.
I am using websql to store data in a phonegap application. One of table have a lot of data say from 2000 to 10000 rows. So when I read from this table, which is just a simple select statement it is very slow. I then debug and found that as the size of table increases the performance deceases exponentially. I read somewhere that to get performance you have to divide table into smaller chunks, is that possible how?
One idea is to look for something to group the rows by and consider breaking into separate tables based on some common category - instead of a shared table for everything.
I would also consider fine tuning the queries to make sure they are optimal for the given table.
Make sure you're not just running a simple Select query without a where clause to limit the result set.
i have an dataset around 1000 records in it. i have made changes around 50 rows in dataset,
i have created an new
dataset dsnew= ds.GetChanges();
now this dsNew would contain all the new 50 rows which we made changes, now i want to update these values to Database,
here i do not want to call 5o times my update command or stored procdure to update my values to table which would really decrease the performance
is there any better way to solve it.
Thanks Prince
This age old request to MS, but still you can try for following options,
ADO.Net batch update.
Note : For insertion you can use SQL Bulk Copy,