How do I optimize a SQL query count?

How do I optimize a SQL query count?

group by drastically reduces the number of rows, so this drastically reduce the number of fetches from t too:

1. First, fetch each row of file_item => 13M rows.
2. For each returned row, fetch a row of family matching f.id = p.
3. Group by type.id => 10 rows.
4. For each returned row, fetch a row of type matching f.

How to optimize query MySQL?

Optimize Queries With MySQL Query Optimization Guidelines

1. Avoid using functions in predicates.
2. Avoid using a wildcard (%) at the beginning of a predicate.
3. Avoid unnecessary columns in SELECT clause.
4. Use inner join, instead of outer join if possible.
5. Use DISTINCT and UNION only if it is necessary.

How can I improve my join query performance?

Performance Considerations for Join Queries

1. Specify the largest table first. This table is read from disk by each Impala node and so its size is not significant in terms of memory usage during the query.
2. Next, specify the smallest table.
3. Join the next smallest table, then the next smallest, and so on.

Why SQL count is slow?

Counting tables with large amount of data may be very slow, sometimes it takes minutes; it also may generate deadlock on a busy server. I want to display real values, NOLOCK is not an option. The servers I use is SQL Server 2005 or 2008 Standard or Enterprise – if it matters.

Is count distinct bad?

In MySQL < 5.5, SELECT COUNT(DISTINCT(xyz)) has really bad performance. SELECT COUNT(*) FROM (SELECT DISTINCT base_dir FROM {boost_cache} GROUP BY base_dir) AS counted; Note that an alias (“AS counted”) is required. This query takes 1-2 seconds on the same test database.

Is count query slow?

Writing count(1) or count(id) are actually slower than count(*) , because they have to test if the argument IS NULL or not ( count , like most aggregates, ignores NULL arguments). So there is nothing to be gained by avoiding the “ * ”.

Are there any good tips for query optimization?

There are many literature and internet publications on techniques and best practices of query optimization, covering all available database management systems, like Oracle and MySQL. But I decided to share my own experience in the field with the focus on SQL Server query optimization tips.

How to optimize the longest running SQL queries?

You can run SQL Server Profiler from SQL Server Management Studio: go to Tools > SQL Server Profiler Using Profiler, you can set filters to choose the longest running queries. For this, we need to perform the following steps: Create a new trace file and go to the Events Selection in a Trace Properties window. Click the Custom Filters button.

How is execution plan used to optimize SQL?

Execution plan also can show you missing indexes that could improve performance and thus optimize SQL query. It would look like this: Apart from showing the index that needs to be added, plan also shows what kind of effect we will get from it. In this case, it will increase performance on 38%.

How to analyze the execution of a query?

Query execution analysis: Execution Plan After we detected the problematic queries, we can start analyzing how they are executed. One of the ways to analyze a query is to use Execution Plan.