I'm using the transaction in .net. I use to insert data into four tables with different methods.
since it is order inflow method, busy in peak hours. The table used for order submission, the same table used for bulk order processing and batch job processing at the same time. so sometime we are getting timeout in any of the above 3 areas.
Mean to say single table used in major 3 transaction areas same time.
order submission.(insert operation)
Job(updating a column)
Bulk order processing(updating a column)
Is that due to locking in order submission affect other transaction also.
Nolock is not used in transactions.
Related
Environment: Oracle 12C
Got a table with about 10 columns which include few clob and date columns. This is a very busy table for an ETL process as described below-
Flat files are loaded into the table first, then updated and processed. The insert and updates happen in batches. Millions of records are inserted and updated.
There is also a delete process to delete old data based on a date field from the table. The delete process runs as a pl/sql procedure and deletes from the table in a loop fetching first n records only based on date field.
I do not want the delete process to interfere with the regular insert/update . What is the best practice to code the delete so that it has minimal impact on the regular insert/update process ?
I can also partition the table and delete in parallel since each partition uses its own rollback segment but am looking for a simpler way to tune the delete process.
Any suggestions on using a special rollback segment or other tuning tips ?
The first thing you should look for is to decouple various ETL processes so that you need not do all of them together or in a particular sequence. Thereby, removing the dependency of the INSERTS/UPDATES and the DELETES. While a insert/update you could manage in single MERGE block in your ETL, you could do the delete later by simply marking the rows to be deleted later, thus doing a soft delete. You could do this as a flag in your table column. And use the same in your application and queries to filter them out.
By doing the delete later, your critical path of the ETL should minimize. Partitioning the data based on date range should definitely help you to maintain the data and also make the transactions efficient if it's date driven. Also, look for any row-by-row thus slow-by-slow transactions and make them in bulk. Avoid context switching between SQL and PL/SQL as much as possible.
If you partition the table as a date range, then you could look into DROP/TRUNCATE partition which will discard the rows stored in that partition as a DDL statement. This cannot be rolled back. It executes quickly and uses few system resources (Undo and Redo). You can read more about it in the documentation.
We have a stored procedure which loads order details about an order. We always want the latest information about an order, so order details for the order are regenerated every time, when the stored procedure is called. We are using SQL Server 2016.
Pseudo code:
DELETE by clustered index based on order identifier
INSERT into the table, based on a huge query containing information about order
When multiple end-users are executing the stored procedure concurrently, there is a blocking created on orderdetails table. Once the first caller is done, second caller is queued, followed by third caller. So, the time for the generation of the orderdetails increases as time goes by. This is happening especially in the cases of big orders containing details rows in > 100k or 1 or 2 million, as there is table level lock is happening.
The approach we took
We partitioned the table based on the last digit of the order identifier for concurrent orderdetails loading. This improves the performance in the case of first time orderdetails loading, as there are no deletes. But, second time onwards, INSERT in first session is causing blocking for other sessions DELETE. The other sessions are blocked till first session is done with INSERT.
We are considering creation of separate orderdetails table for every order to avoid this concurrency issues.
Question
Can you please suggest some approach, which will support concurrent DELETE & INSERT scenario ?
We solved the contention issue by going for temporary table for orderdetails. We found that huge queries are taking longer SELECT time and this longer time was contributing to longer table level locks on the orderdetails table.
So, we first loaded data into temporary table #orderdetail and then went for DELETE and INSERT in the orderdetail table.
As the orderdetail table is already partitioned, DELETE were faster and INSERT were happening in parallel. INSERT was also very fast here, as it is simple table scan from #orderdetail table.
You can give a look to the Hekaton Engine. It is available even in SQL Server Standard Edition if you are using SP1.
If this is too complicated for implementation due to hardware or software limitations, you can try to play with the Isolation Levels of the database. Sometimes, queries that are reading huge amount of data are blocked or even deadlock victims of queries which are modifying parts of these data. You can ask yourself do you need to guarantee that the data read by the user is valid or you can afford for example some dirty reads?
I have triggers on multiple tables that capture updates to a table (Capture Table). Once that insert is complete the trigger completes and control returns to the calling application. It's expected that this capture table will receive about 1.75 million records per day.
I then have a Windows service that runs and takes the data from the Capture Table, adds some context by referencing other tables in our database, then inserts records into a notification table that is used by another process.
Our Capture Table has an IDENTITY column and a DATETIME to help with sequencing. For the DATETIME, we set a variable to GETDATE() and use the variable so that all records in the same transaction will have the exact same DATETIME.
I am looking at making the process more robust. At this point the Windows service calls a stored procedure and processes one transaction at a time in sequence. This could become a bottleneck. We may need to process multiple transactions at the same time.
How can I guarantee the sequence is the same between the Capture Table and the notification table? It’s critical that the records stay in the same order. Thanks for your input!
I want to place DB2 Triggers for Insert, Update and Delete on DB2 Tables heavily used in parallel online Transactions. The tables are shared by several members on a Sysplex, DB2 Version 10.
In each of the DB2 Triggers I want to insert a row into a central table and have one background process calling a Stored Procedure to read this table every second to process the newly inserted rows, ordered by sequence of the insert (sequence number or timestamp).
I'm very concerned about DB2 Index locking contention and want to make sure that I do not introduce Deadlocks/Timeouts to the applications with these Triggers.
Obviously I would take advantage of DB2 Features to reduce locking like rowlevel locking, but still see no real good approach how to avoid index contention.
I see three different options to select the newly inserted rows.
Put a sequence number in the table and the store the last processed sequence number in the background process. I would do the following select Statement:
SELECT COLUMN_1, .... Column_n
FROM CENTRAL_TABLE
WHERE SEQ_NO > 'last-seq-number'
ORDER BY SEQ_NO;
Locking Level must be CS to avoid selecting uncommited rows, which will be later rolled back.
I think I need one Index on the table with SEQ_NO ASC
Pro: Background process only reads rows and makes no updates/deletes (only shared locks)
Neg: Index contention because of ascending key used.
I can clean-up processed records later (e.g. by rolling partions).
Put a Status field in the table (processed and unprocessed) and change the Select as follows:
SELECT COLUMN_1, .... Column_n
FROM CENTRAL_TABLE
WHERE STATUS = 'unprocessed'
ORDER BY TIMESTAMP;
Later I would update the STATUS on the selected rows to "processed"
I think I need an Index on STATUS
Pro: No ascending sequence number in the index and no direct deletes
Cons: Concurrent updates by online transactions and the background process
Clean-up would happen in off-hours
DELETE the processed records instead of the status field update.
SELECT COLUMN_1, .... Column_n
FROM CENTRAL_TABLE
ORDER BY TIMESTAMP;
Since the table contains very few records, no index is required which could create a hot spot.
Also I think I could SELECT with Isolation Level UR, because I would detect potential uncommitted data on the later delete of this row.
For a Primary Key index I could use GENERATE_UNIQUE,which is random an not ascending.
Pro: No Index hot spot and the Inserts can be spread across the tablespace by random UNIQUE_ID
Con: Tablespace scan and sort on every call of the Stored Procedure and deleting records in parallel to the online inserts.
Looking forward what the community thinks about this problem. This must be a pretty common problem e.g. SAP should have a similar issue on their Batch Input tables.
I tend to favour Option 3, because it avoids index contention.
May be there is still another solution in your minds out there.
I think you are going to have numerous performance problems with your various solutions.
(I know premature optimazation is a sin, but experience tells us that some things are just not going to work in a busy system).
You should be able to use DB2s autoincrement feature to get your sequence number, with little or know performance implications.
For the rest perhaps you should look at a Queue based solution.
Have your trigger drop the operation (INSERT/UPDATE/DELETE) and the keys of the row into a MQ queue,
Then have a long running backgound task (in CICS?) do your post processing as its processing one update at a time you should not trip over yourself. Having a single loaded and active task with the ability to batch up units of work should give you a throughput in the order of 3 to 5 hundred updates a second.
I have a SQL Server 2012 table that will contain 2.5 million rows at any one time. Items are always being written into the table, but the oldest rows in the table get truncated at the end of each day during a maintenance window.
I have .NET-based reporting dashboards that usually report against summary tables though on the odd occasion it does need to fetch a few rows from this table - making use of the indexes set.
When it does report against this table, it can prevent new rows being written to this table for up to 1 minute, which is very bad for the product.
As it is a reporting platform and the rows in this table never get updated (only inserted - think Twitter streaming but for a different kind of data) it isn't always necessary to wait for a gap in the transactions that cause rows to get inserted into this table.
When it comes to selecting data for reporting, would it be wise to use a SNAPSHOT isolation level within a transaction to select the data, or NOLOCK/READ UNCOMITTED? Would creating a SQLTransaction around the select statement cause the insert to block still? At the moment I am not wrapping my SQLCommand instance in a transaction, though I realise this will still cause locking regardless.
Ideally I'd like an outcome where the writes are never blocked, and the dashboards are as responsive as possible. What is my best play?
Post your query
In theory a select should not be blocking inserts.
By default a select only takes a shared lock.
Shared locks are acquired during read operations automatically and prevent the user from modifying data.
This should not block inserts to otherTable or joinTable
select otherTable.*, joinTable.*
from otherTable
join joinTable
on otherTable.jionID = joinTable.ID
But it does have the overhead of acquiring a read lock (it does not know you don't update).
But if it is only fetching a few rows from joinTable then it should only be taking a few shared locks.
Post your query, query plan, and table definitions.
I suspect you have some weird stuff going on where it is taking a lot more locks than it needs.
It may be taking lock on each row or it may be escalating to page lock or table lock.
And look at the inserts. Is it taking some crazy locks it does not need to.