How to find the SQL statements that caused tempdb growth? The tempdb of a server (SQL Server 2008) increases to 500GB+ several times every month. Is it possible to find out which SQL statements caused this problem? The problem is usually not caused by create table #temp...; insert into #temp... or select ... into #temp... but complex joins.

The Initial Size of some of the tempdb files is also automatically set to much bigger values every time. How to prevent it?

Sometime the cached plans prevent resizing/shrinking the files. How to find which one hold the tempdb?
There are three DMVs you can use to track tempdb usage:


sys.dm_db_task_space_usage
sys.dm_db_session_space_usage
sys.dm_db_file_space_usage


The first two will allow you to track allocations at a query &amp; session level. The third tracks allocations across version store, user and internal objects.

The following example query will give you allocations per session:

SELECT
  sys.dm_exec_sessions.session_id AS [SESSION ID]
  ,DB_NAME(database_id) AS [DATABASE Name]
  ,HOST_NAME AS [System Name]
  ,program_name AS [Program Name]
  ,login_name AS [USER Name]
  ,status
  ,cpu_time AS [CPU TIME (in milisec)]
  ,total_scheduled_time AS [Total Scheduled TIME (in milisec)]
  ,total_elapsed_time AS    [Elapsed TIME (in milisec)]
  ,(memory_usage * 8)      AS [Memory USAGE (in KB)]
  ,(user_objects_alloc_page_count * 8) AS [SPACE Allocated FOR USER Objects (in KB)]
  ,(user_objects_dealloc_page_count * 8) AS [SPACE Deallocated FOR USER Objects (in KB)]
  ,(internal_objects_alloc_page_count * 8) AS [SPACE Allocated FOR Internal Objects (in KB)]
  ,(internal_objects_dealloc_page_count * 8) AS [SPACE Deallocated FOR Internal Objects (in KB)]
  ,CASE is_user_process
             WHEN 1      THEN 'user session'
             WHEN 0      THEN 'system session'
  END         AS [SESSION Type], row_count AS [ROW COUNT]
FROM 
  sys.dm_db_session_space_usage
INNER join
  sys.dm_exec_sessions
ON  sys.dm_db_session_space_usage.session_id = sys.dm_exec_sessions.session_id


If you want to track usage over a period of time, consider collecting data with sp_whoisactive, as demonstrated by Kendra Little.