I've got a sql that uses FETCH and OFFSET to choose between specific rows, however i'm concerned about the possible performance and cost of running theese queries within tables with lots of rows. Looking at FETCH AND OFFSET in sql server 2012 it seems like it has bad performance by looking here http://sqlblogcasts.com/blogs/sqlandthelike/archive/2010/11/10/denali-paging-is-it-win-win.aspx and as you also can see the memory used was 44mb for the 10 000 row table.
Questions:
1.should i worry about the performance using this method within sql server 2014 when the table grows?
2.have they done anything since to improve this?
3.Is there any alternative way of doing this that is considered better?
Hi I know that this is an old question but, if you read http://social.technet.microsoft.com/wiki/contents/articles/23811.paging-a-query-with-sql-server.aspx you will find an excellent analysis about using FECHT and OFFSET vs ROW_NUMBER and how was improved since the SP1 of MSSSQL 2012.
Related
The query below takes about a minute to run on my MySQL instance (running on a fairly beefy machine with 64G memory, 2T disc, 2.30Ghz CPU with 8 cores and 16 logical, and the query is running on localhost). This same query runs in less than a second on a SQL Server database I have access to. Unfortunately, I do not have access to the SQL Server host or the DBA, etc.
select min(visit_start_date)
from visit_occurrence;
The table has been set to ENGINE=MyISAM and default-storage-engine=INNODB and innodb_buffer_pool_size=16G are set in my.ini.
Is there some configuration I could be missing that would cause this query to run so slowly on MySQL? How can I fix it?
I have a large number of tables and queries I will need to support so I would really like to be able to fix this issue globally rather than having to create indexes everywhere I have slow queries.
The SQL Server database does not seem to have an index on the column being queried as shown below.
EDIT:
Untagged MS Sql Server, I had tagged it hoping for the help of our MS Sql Server colleagues with information that Sql Server had some way of structuring data and/or queries that would make this type of query run faster on that platform v other such as MySql
Removed image of code to more closely conform with community standards
You never know if there is a magic go-faster button if you don't ask (ENGINE=MyISAM is sometimes kind of like a magic go-faster button for some queries in MySql). I'm kind of fishing for a potential hardware or clustering solution here. Is Apache Ignite a potential solution here?
Thanks again to the community for all of your support and help. I hope this fixes most of the issues that have been raised for this post.
SECOND EDIT:
Is the partitioning/sharding described in the links below a potential solution here?
https://user3141592.medium.com/how-to-scale-mysql-42ebd2841fa6
https://dev.mysql.com/doc/refman/8.0/en/partitioning-overview.html
THIRD EDIT: A note on community standards.
Part of our community standards is explicitly to be welcoming, inclusive, and to be nice.
https://stackoverflow.blog/2018/04/26/stack-overflow-isnt-very-welcoming-its-time-for-that-to-change/?fbclid=IwAR1gr6r2qmXs506SAV3H_h6H8LoFy3mlXucfa-fqiiEXMHUR3aF_tdoZGsw
https://meta.stackexchange.com/questions/240839/the-new-new-be-nice-policy-code-of-conduct-updated-with-your-feedback).
The MS Sql Server tag was used here as one of the systems I'm comparing is MS Sql Server. We're really working with very limited information here. I have two systems: My MySql system, which is knowable as I'm running it, and the MS Sql Server running the same database in someone else's system that I have very little information about (all I have is a read only sql prompt). I am comparing apples and oranges: The same query runs well on the orange (MS Sql Server) and does not run well on the apple (My MySql instance). I'd like to know why so I can make an informed decision about how to get my queries to run in a reasonable amount of time. How do I get my apple to look like an orange? Do I switch to MS Sql Server? Do I need to deploy on different hardware? Is the other system running some kind of in memory caching system on top of their database instance? Most of these possibilities would require a non trivial amount of time to explore and validate. So yes, I would like help from MS Sql Server experts that might know if there are caching options, transactional v warehouse options, etc. that could be set that would make a world of difference, that would be magic go-fast buttons.
The magic go-fast button comment was perhaps a little bit condescending.
The picture showing the indexes was shown as I was just trying to make the point that the other system does not seem to have an index on the column being queried. I this case a picture was worth a thousand words.
If the table says ENGINE=MyISAM, then that is what counts. In almost all cases, this is a bad choice. innodb_buffer_pool_size=16G is not relevant except that it robs memory from MyISAM.
default-storage-engine=INNODB is relevant only when creating a table explicitly specifying the ENGINE=.
Are some of your tables MyISAM and some are InnoDB? How much RAM do you have?
Most performance solutions necessarily involve an INDEX. Please explain why you can't afford an index. It could turn that query into less than 10ms, regardless of the number of rows in the table.
Sorry, but I don't accept "rather than having to create indexes everywhere I have slow queries".
Changing tables from MyISAM to InnoDB will, in some cases help with performance. Suggest you change the engine as you add the indexes.
Show us some more queries, we can help you decide what indexes are needed. select min(visit_start_date) from visit_occurrence; needs INDEX(date); other queries may not be so trivial. Do not fall into the trap of "indexing every column".
More
In MySQL...
A single connection only uses one core, so more cores only helps when you have more connections. (Some tiny exceptions exist in MySQL 8.0.)
Partitioning rarely helps with performance; do use that without getting advice. (PS: BY RANGE is perhaps the only useful variant.)
Replication is for read-scaling (and backup and ...)
Sharding is for write-scaling. It requires a bunch of extra architectural things -- such as routing queries to the appropriate servers. (MariaDB has Spider and FederatedX as possible tools.) In any case, sharding is a non-trivial undertaking.
Clustering is for HA (High Availability, auto-failover, etc), while helping some with read and write scaling. Cf: Galera, InnoDB Cluster.
Hardware is rarely more than a temporary solution to performance issues.
Caching leads to potentially inconsistent results, so beware. Also, consider my mantra "don't bother putting a cache in front of a cache".
(I can advise further on any of these topics.)
Whether in MyISAM or InnoDB. or even SQL Server, your query
select min(visit_start_date) from visit_occurrence;
can be satisfied almost instantaneously by this index, because it uses a so-called loose index scan.
CREATE INDEX visit_start_date ON visit_occurrence (visit_start_date);
A query with an aggregate function like MIN() is always a GROUP BY query. But if the GROUP BY clause isn't present in the SQL statement, the server groups by the entire table.
You mentioned a query that can be satisfied immediately when using MyISAM. That's SELECT COUNT(*) FROM whatever_table. Behind the scenes MyISAM keeps table metadata showing the total number of rows in the table, so that query comes back right away. The transactional storage engine InnoDB doesn't do that. It supports so much concurrency that its designers didn't include the total row count in their metadata, because it would be wrong in so many circumstances that it wasn't worth the risk.
Index design isn't a black art. But it is an art informed by the kind of measurements we get from EXPLAIN (or ANALYZE or EXPLAIN ANALYZE). A basic truth of database-driven apps (in any make of database server) is that indexing needs to be revisited as the app grows. The good news: changing, adding, or dropping indexes doesn't change your data.
Can anyone explain to me why there is a dramatic difference in performance between MySQL and SQL Server for this simple select statement?
SELECT email from Users WHERE id=1
Currently the database has just one table with 3 users. MySQL time is on average 0.0003 while SQL Server is 0.05. Is this normal or the MSSQL server is not configured properly?
EDIT:
Both tables have the same structure, primary key is set to id, MySQL engine type is InnoDB.
I tried the query with WITH(NOLOCK) but the result is the same.
Are the servers of the same level of power? Hardware makes a difference, too. And are there roughly the same number of people accessing the db at the same time? Are any other applications using the same hardware (databases in general should not share servers with other applications).
Personally I wouldn't worry about this type of difference. If you want to see which is performing better, then add millions of records to the database and then test queries. Database in general all perform well with simple queries on tiny tables, even badly designed or incorrectly set up ones. To know if you will have a performance problem you need to test with large amounts of data and many simulataneous users on hardware similar to the one you will have in prod.
The issue with diagnosing low cost queries is that the fixed cost may swamp the variable costs. Not that I'm a MS-Fanboy, but I'm more familiar with MS-SQL, so I'll address that, primarily.
MS-SQL probably has more overhead for optimization and query parsing, which adds a fixed cost to the query when decising whether to use the index, looking at statistics, etc. MS-SQL also logs a lot of stuff about the query plan when it executes, and stores a lot of data for future optimization that adds overhead
This would all be helpful when the query takes a long time, but when benchmarking a single query, seems to show a slower result.
There are several factors that might affect that benchmark but the most significant is probably the way MySQL caches queries.
When you run a query, MySQL will cache the text of the query and the result. When the same query is issued again it will simply return the result from cache and not actually run the query.
Another important factor is the SQL Server metric is the total elapsed time, not just the time it takes to seek to that record, or pull it from cache. In SQL Server, turning on SET STATISTICS TIME ON will break it down a little bit more but you're still not really comparing like for like.
Finally, I'm not sure what the goal of this benchmarking is since that is an overly simplistic query. Are you comparing the platforms for a new project? What are your criteria for selection?
I have run into problem with selecting large data from SQL Server. I have a view with 200 columns and 200 000 rows. And I am using the view for Solr indexing.
I tried to select data with paging but it took a lot of time(more then 6 hours). Now i am selecting it without paging and it take 1 hour. But SQL Server takes a lot of memory.
What is the best method or approach to select large data in such situations from SQL Server 2008 R2?
Thanks in advance.
200k rows is not that much and definitely shouldn't take 6 hours, not even 1 hour.
I did not understant if the problem is on the actuall select or bringing the result to the application.
I would recomend running the select with NOLOCK to ignore blockings, maybe your table is beeing accessed by other processes when you are running the query
SELECT * FROM TABLE WITH(NOLOCK)
If the problem is on bringing the data to the application you'll need to provide mroe details on how you are doing it
I'd suggest taking a look at your execution plan. Look at the properties in the very first operator and see if you're getting "Good Enough Plan Found" or a timeout. If it's the latter, you may have a very complicated view or you may be nesting views (a view calling a view). See what you can do to simplify the query in order to give the optimizer a chance to create a good execution plan.
Can any one guide me about my query?, i m making application for banking sector with fuzzy logic. i have to import table with 100 million rows daily. and i am using MySql for this application which is processing slowly. so is there any another server for handling my database which can access fast?
We roughly load about half that many rows a day in our RDBMS (Oracle) and it would not occur to me to implement such a thing without access to DBA knowledge about my RDBMS. We fine-tune this system several times a month and we still encounter new issues all the time. This is such a non-trivial task that the only valid answer is:
Don't play around, have your managers get a DBA who knows their business!
Note: Our system has been in place for 10 years now. It hasn't been built in a day...
100 million rows daily?
You have to be realistic. I doubt any single instance of any database out there can handle this type of thouroughput efficiently. You should probably look at clustering options and other optimising techniques such as splitting data in two diffent DB's (sharding).
MySQL Enterprise has a bunch of features built-in that could ease and moniter the clustering process, but I think MySQL community edition supports it too.
Good-luck!
How are you doing it?
One hugh transaction?
Perhaps try to make small transactions in chunks of 100 or 1000.
Is there an index on that table? Drop the index before starting the improt (if that is possible due to unique costraints etc.) and rebuild the index after the import.
An other option would perhaps be an in memory database.
Well it seems your business' main logic does not depend on importing those 100mio rows into a database, otherwise you wouldn't be stuck with doing this by yourself, right? (correct me if I'm wrong)
Are you sure you need to import those rows into a database when the main business doesn't need to? What kind of questions are you going to ask of the date? Can't you maybe keep the log files on a bunch of servers and query them with eg Hadoop? Or can you aggregate the information contained in the log files and only store a condensed version?
I'm also asking this because it sounds like you're planning to perform some at least moderately sophisticated analysis on the data and the trouble with this amount of data won't stop once you have it in a DB.
We are using a mysql database w/ about 150,000 records (names) total. Our searches on the 'names' field is done through an autocomplete function in php. We have the table indexed but still feel that the searching is a bit sluggish (a few full seconds vs. something like Google Finance w/ near-instant response). We came up w/ 2 possibilities, but wanted to get more insight:
Can we create a bunch (many thousands or more) of stored procedures to speed up searches, or will creating that many stored procedures bog-down the db?
Is there a faster alternative to mysql for "select" statements (speed on inserting & updating rows isn't too important so we can sacrifice that, if necessary). I've vaguely heard of BigTable & others that don't support JOIN statements....we need JOIN statements for some of our other queries we do.
thx
Forget about stored procedures. They wont do any good for you.
Mysql is good choice, it's often considered as fastest RDBMS. And there is no need to look for 'faster alternative to select statement'.
Abnormal query execution time you mentioned is a result of server misconfiguration or wrong database schema, or both. Please read this response on serverfault or update your question here: provide server configuration, part of database schema and problem query along with explain select ...
You need to cache the information in memory to avoid making repeated calls to the database.
Yes, you need to expire the cache if you change the data, but as you said, that's not common, so you can even do that on a semi-automated basis and not worry about it if necessary. You should check out this MySQL.com article, as well as perhaps explore the MEMORY storage engine (sorry, new and can't post more than one hyperlink per post?!) which takes a little bit of coding around to use but can be extremely efficient.
What's the actual query time (vs page time)? On a reasonably modern server that's not loaded to hell, MySQL should be able to do an autocomplete query on 150k rows much, much, faster than two seconds. Missing some indexes?