I have an SQL query as simple as:
select * from recent_cases where user_id=1000000 and case_id=10095;
It takes up to 0.4 seconds to execute it in Oracle. And when I do 20 requests in a row, it takes > 10s.
The table 'recent_cases' has 4 columns: ID, USER_ID, CASE_ID and VISITED_DATE. Currently there are only 38 records in this table.
Also, there are 3 indexes on this table: on ID column, on USER_ID column, and on (USER_ID, CASE_ID) columns pair.
Any ideas?
One theory -- the table has a very large data segment and high water mark near the end, but the statistics are not prompting the optimiser to use an index. Therefore you're getting a slow full table scan. You could ALTER TABLE ... MOVE and rebuild the indexes to fix such a problem, or COALESCE it.
Oracle Databases have a function called "analyze table". This function can speed up select statements a lot, even if there are just a few rows in the table.
Here are some links which might help you:
http://www.dba-oracle.com/t_oracle_analyze_table.htm
http://docs.oracle.com/cd/B28359_01/server.111/b28310/general002.htm
Related
Is there an efficient way to update rows of a table that has no indexes and no partitions (and ~50millions rows)?
I have a date field LOAD_DTTM and values of this field for rows that require update (around 2000 distinct dates).
WIll update be faster if i specify a date in a WHERE clause along with the UNIQUE_ID of a row?
If you want to update all, or a large number, of the rows then the quickest way is:
create table my_table_copy as
select ... -- all the columns, updating values as required
from my_table;
drop table my_table;
rename my_table_copy to my_table;
If your table had any indexes, constraints or triggers you would now need to re-add them - but it seems you don't have that issue!
You could create a PL/SQL procedure that loops and update and commit the table every n row count -- Say every 20.000 rows. I do not advise to update the full table as it will create a lock for a looong time and expose you to data loss in case of external factors.
The answer is NO.
Even if you specify both conditions in your WHERE clause as you stated, it won't help you to avoid a full scan of your table.
Even if one of your criteria will uniquely identify the row, it still won't help.
There is a real example tested on Oracle 12C ver.2 similar to your case. No indexes, no partitions, nothing. Just plain table with 4 columns
I have a table with 18mn records.
I also have CUSTOMER_ID which is a UNIQUE identifier for a row.
I also have ORDER_DATE column there.
Even if I do the query that you mentioned
update hit set status = 1 where customer_id = 408518625844 and order_date = '09-DEC-19';
it won't help me to avoid a full table scan. See below Execution Plan. Therefore under conditions, you've specified, you will be always getting the slowest execution time possible. Full Table Scan on 50mn rows is actually the worst-case scenario.
And pay attention to that Cost, it is 26539 on 18mn rows.
So if you have 50mn rows we can easily expect much more Cost for your query
I have approx 820,000 records in my SQL Server table and it is taking 5 seconds to select the data from the table. The table has one clustered index on a time column that could be NULL (as of now it does not contain any NULL value). Why is it taking 5 to 6 seconds to fetch only this much records?
What did you mean by 'select the data'? If you are fetching so many records in management studio (displaying all the records) most of this 6 seconds is consumed by showing you all the rows. If it is the case just insert the records to a temp table. It will be much faster.
I recomend you this:
1.Check if you are using Clustered and Non-Clustered in you columns (best way I think with a sp_help NameTable).
2.When you using comand "select" specific always all name columns (never use Select * From ..... ).
3.If you are using SSMS check in tools SQL Execution Plan , with this tool you can make simple review your TSQL (you can see cost
each query you make.
4.Dont use "convert(...." in clause WHERE , for example .. Where Convert(int,NameColum)=100.
I have a table named [cwbOrder] that currently has 1.277.469 rows. I am using SQL Server 2014 and I am doing these tests on a UAT environment, on production this query takes a little bit longer.
If I try selecting all of the rows like using:
SELECT * FROM cwbOrder
It takes 24 seconds to retrieve all of the data from the table. I have read about how it is important to index columns used in the predicates (WHERE), but I still cannot understand how does a simple select take 24 seconds.
Using this table in other more complex queries generates a lot of extra workload for the query, although I have created the JOINs on indexed columns. Additionally I have selected only 2 columns from this table then JOINED it to another table and this operation still takes a significantly long amount of time. As an example please consider the below query:
Below I have attached the index structure of both tables, to illustrate the matter:
PK_cwbOrder is the index on the id_cwbOrder column in the cwbOrder table.
Edit 1: I have added the execution plan for the query in which I join the cwbOrder table with the cwbAction table.
Is there any way, considering the information above, that I can make this query faster?
There are many reasons why such a select could be slow:
The row size or number of rows could be very large, requiring a lot of time to transport or delay.
Other operations on the table could have locks on the table.
The database server or network could be very busy.
The "table" could really be a view that is running a complicated query.
You can test different aspects. For instance:
SELECT TOP 10 <one column here>
FROM cwbOrder o
This returns a very small result set and reads just a small part of the table. This reads the entire table but returns a small result set:
SELECT COUNT(*)
FROM cwbOrder o
i need advice how to get fastest result for querying on big size table.
I am using SQL Server 2012, my condition is like this:
I have 5 tables contains transaction record, each table has 35 millions of records.
All tables has 14 columns, the columns i need to search is GroupName, CustomerName, and NoRegistration. And I have a view that contains 5 of all these tables.
The GroupName, CustomerName, and NoRegistration records is not unique each tables.
My application have a function to search to these column.
The query is like this:
Search by Group Name:
SELECT DISTINCT(GroupName) FROM TransactionRecords_view WHERE GroupName LIKE ''+#GroupName+'%'
Search by Name:
SELECT DISTINCT(CustomerName) AS 'CustomerName' FROM TransactionRecords_view WHERE CustomerName LIKE ''+#Name+'%'
Search by NoRegistration:
SELECT DISTINCT(NoRegistration) FROM TransactionRecords_view WHERE LOWER(NoRegistration) LIKE LOWER(#NoRegistration)+'%'
My question is how can i achieve fastest execution time for searching?
With my condition right now, every time i search, it took 3 to 5 minutes.
My idea is to make a new tables contains the distinct of GroupName, CustomerName, and NoRegistration from all 5 tables.
Is my idea is make execution time is faster? or any other idea?
Thank you
EDIT:
This is query for view "TransactionRecords_view"
CREATE VIEW TransactionRecords_view
AS
SELECT * FROM TransactionRecords_1507
UNION ALL
SELECT * FROM TransactionRecords_1506
UNION ALL
SELECT * FROM TransactionRecords_1505
UNION ALL
SELECT * FROM TransactionRecords_1504
UNION ALL
SELECT * FROM TransactionRecords_1503
You must show sql of TransactionRecords_view. Do you have indexes? What is the collation of NoRegistration column? Paste the Actual Execution Plan for each query.
Ok, so you don't need to make those new tables. If you create Non-Clustered indexes based upon these fields it will (in effect) do what you're after. The index will only store data on the columns that you indicate, not the whole table. Be aware, however, that indexes are excellent to aid in SELECT statements but will negatively affect any write statements (INSERT, UPDATE etc).
Next you want to run the queries with the actual execution plan switched on. This will show you how the optimizer has decided to run each query (in the back end). Are there any particular issues here, are any of the steps taking up a lot of the overall operator cost? There are plenty of great instructional videos about execution plans on youtube, check them out if you haven't looked at exe plans before.
Did you try to check if there were missing indexes with the actual execution plan ?
Moreover, as you use clause on varchar, I've heard about Full-Text Search.. maybe it can be useful for you :
https://msdn.microsoft.com/en-us/library/ms142571(v=sql.120).aspx
I have a table
Books(BookId, Name, ...... , PublishedYear)
I do have about 30 fields in my Books table, where BookId is the primary key (Identity column). I have about 2 million records for this table.
I know select * is evil performance killer..
I have a situation to select range of rows or all the rows having all the columns in it.
Select * from Books;
this query takes more than 2 seconds to scan through the data page and get all the records. On checking the execution it still uses the Clustered index scan.
Obviously 2 seconds my not be that bad, however when this table has to be joined with other tables which is executed in batch is taking time over 15 minutes (There are no duplicate records though on the final result at completion as the count is matching). The join criteria is pretty simple and yields no duplication.
Excluding this table alone has the batch execution completed in sub seconds.
Is there a way to optimize this having said that I will have to select all the columns :(
Thanks in advance.
I've just run a batch against my developer instance, one SELECT specifying all Columns and one using *. There is no evidence (nor should there) that there is any difference aside from the raw parsing of my input. If I remember correctly, that old saying really means: Do not SELECT columns you are not using, they use up resources without benefit.
When you try to improve performance in your code, always check your assumptions, they might only apply to some older version (of sql server etc) or other method.