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Understand and resolve blocking problems

  • Άρθρο

Applies to: Azure SQL Database SQL database in Fabric

The article describes blocking in Azure SQL Database and Fabric SQL database, and demonstrates how to troubleshoot and resolve blocking.

Objective

In this article, the term connection refers to a single logged-on session of the database. Each connection appears as a session ID (SPID), or session_id in many DMVs. Each of these SPIDs is often referred to as a process, although it isn't a separate process context in the usual sense. Rather, each SPID consists of the server resources and data structures necessary to service the requests of a single connection from a given client. A single client application might have one or more connections. From the perspective of Azure SQL Database, there's no difference between multiple connections from a single client application on a single client computer and multiple connections from multiple client applications or multiple client computers; they're atomic. One connection can block another connection, regardless of the source client.

For information on troubleshooting deadlocks, see Analyze and prevent deadlocks in Azure SQL Database and Fabric SQL database.

Note

This content is focused on Azure SQL Database. Azure SQL Database is based on the latest stable version of the Microsoft SQL Server database engine, so much of the content is similar though troubleshooting options and tools might differ. For more on blocking in SQL Server, see Understand and resolve SQL Server blocking problems. Fabric SQL database shares many features with Azure SQL Database. For more information on performance monitoring, see Monitor SQL database in Microsoft Fabric.

Understand blocking

Blocking is an unavoidable and by-design characteristic of any relational database management system (RDBMS) with lock-based concurrency. Blocking in a database in Azure SQL Database occurs when one session holds a lock on a specific resource and a second SPID attempts to acquire a conflicting lock type on the same resource. Typically, the time frame for which the first SPID locks the resource is small. When the owning session releases the lock, the second connection is then free to acquire its own lock on the resource and continue processing. This behavior is normal, and can happen many times throughout the course of a day with no noticeable effect on system performance.

Each new database in Azure SQL Database has the read committed snapshot (RCSI) database setting enabled by default. Blocking between sessions reading data and sessions writing data is minimized under RCSI, which uses row versioning to increase concurrency. However, blocking and deadlocks can still occur in databases in Azure SQL Database because:

  • Queries that modify data might block one another.
  • Queries might run under isolation levels that increase blocking. Isolation levels can be specified in application connection strings, query hints, or SET statements in Transact-SQL.
  • RCSI might be disabled, causing the database to use shared (S) locks to protect SELECT statements run under the read committed isolation level. This can increase blocking and deadlocks.

Snapshot isolation level is also enabled by default for new databases in Azure SQL Database. Snapshot isolation is an additional row-based isolation level that provides transaction-level consistency for data and which uses row versions to select rows to update. To use snapshot isolation, queries or connections must explicitly set their transaction isolation level to SNAPSHOT. This can only be done when snapshot isolation is enabled for the database.

You can identify if RCSI and/or snapshot isolation are enabled with Transact-SQL. Connect to your database in Azure SQL Database and run the following query:

SELECT name, is_read_committed_snapshot_on, snapshot_isolation_state_desc
FROM sys.databases
WHERE name = DB_NAME();
GO

If RCSI is enabled, the is_read_committed_snapshot_on column returns the value 1. If snapshot isolation is enabled, the snapshot_isolation_state_desc column returns the value ON.

The duration and transaction context of a query determine how long its locks are held, and their effect on other queries. SELECT statements run under RCSI don't acquire shared (S) locks on the data being read, and therefore don't block transactions that are modifying data. For INSERT, UPDATE, and DELETE statements, the locks are held during the query, both for data consistency and to allow the query to be rolled back if necessary.

For queries executed within an explicit transaction, the type of locks and duration for which the locks are held are determined by the type of query, the transaction isolation level, and whether lock hints are used in the query. For a description of locking, lock hints, and transaction isolation levels, see the following articles:

When locking and blocking persists to the point where there's a detrimental effect on system performance, it's due to one of the following reasons:

  • A SPID holds locks on a set of resources for an extended period of time before releasing them. This type of blocking resolves itself over time but can cause performance degradation.

  • A SPID holds locks on a set of resources and never releases them. This type of blocking doesn't resolve itself and prevents access to the affected resources indefinitely.

In the first scenario, the situation can be very fluid as different SPIDs cause blocking on different resources over time, creating a moving target. These situations are difficult to troubleshoot using SQL Server Management Studio to narrow down the issue to individual queries. In contrast, the second situation results in a consistent state that can be easier to diagnose.

Optimized locking

Optimized locking is a new Database Engine feature drastically reduces lock memory and the number of locks concurrently required for writes. Optimized locking uses two primary components: Transaction ID (TID) locking (also used in other row versioning features) and lock after qualification (LAQ). It doesn't require any extra configuration.

This article currently applies to the behavior of the Database Engine without optimized locking.

For more information and to learn where optimized locking is available, see Optimized locking.

Applications and blocking

There can be a tendency to focus on server-side tuning and platform issues when facing a blocking problem. However, paying attention only to the database might not lead to a resolution, and can absorb time and energy better directed at examining the client application and the queries it submits. No matter what level of visibility the application exposes regarding the database calls being made, a blocking problem frequently requires both the inspection of the exact SQL statements submitted by the application, and the application's exact behavior regarding query cancellation, connection management, fetching all result rows, and so on. If the development tool doesn't allow explicit control over connection management, query cancellation, query time-out, result fetching, and so on, blocking problems might not be resolvable. This potential should be closely examined before selecting an application development tool for Azure SQL Database, especially for performance sensitive OLTP environments.

Pay attention to database performance during the design and construction phase of the database and application. In particular, the resource consumption, isolation level, and transaction path length should be evaluated for each query. Each query and transaction should be as lightweight as possible. Good connection management discipline must be exercised. Without it, the application can appear to have acceptable performance at low numbers of users, but the performance might degrade significantly as the number of users scales upward.

With proper application and query design, Azure SQL Database is capable of supporting many thousands of simultaneous users on a single server, with little blocking.

Note

For more application development guidance, see Troubleshoot connectivity issues and other errors and Transient Fault Handling.

Troubleshoot blocking

Regardless of which blocking situation we are in, the methodology for troubleshooting locking is the same. These logical separations are what dictates the rest of the composition of this article. The concept is to find the head blocker and identify what that query is doing and why it's blocking. Once the problematic query is identified (that is, what is holding locks for the prolonged period), the next step is to analyze and determine why the blocking is happening. After we understand the reasons why, we can then make changes by redesigning the query and the transaction.

Steps in troubleshooting:

  1. Identify the main blocking session (head blocker)

  2. Find the query and transaction that is causing the blocking (what is holding locks for a prolonged period)

  3. Analyze/understand why the prolonged blocking occurs

  4. Resolve blocking issue by redesigning query and transaction

Now let's dive in to discuss how to pinpoint the main blocking session with an appropriate data capture.

Gather blocking information

To counteract the difficulty of troubleshooting blocking problems, a database administrator can use SQL scripts that constantly monitor the state of locking and blocking in the database in Azure SQL Database. To gather this data, there are essentially two methods.

The first is to query dynamic management objects (DMOs) and store the results for comparison over time. Some objects referenced in this article are dynamic management views (DMVs) and some are dynamic management functions (DMFs). The second method is to use XEvents to capture what is executing.

Gather information from DMVs

Referencing DMVs to troubleshoot blocking has the goal of identifying the SPID (session ID) at the head of the blocking chain and the SQL Statement. Look for victim SPIDs that are being blocked. If any SPID is being blocked by another SPID, then investigate the SPID owning the resource (the blocking SPID). Is that owner SPID being blocked as well? You can walk the chain to find the head blocker then investigate why it's maintaining its lock.

Remember to run each of these scripts in the target database in Azure SQL Database.

  • The sp_who and sp_who2 commands are older commands to show all current sessions. The DMV sys.dm_exec_sessions returns more data in a result set that is easier to query and filter. You can find sys.dm_exec_sessions at the core of other queries.

  • If you already have a particular session identified, you can use DBCC INPUTBUFFER(<session_id>) to find the last statement that was submitted by a session. Similar results can be returned with the sys.dm_exec_input_buffer dynamic management function (DMF), in a result set that is easier to query and filter, providing the session_id and the request_id. For example, to return the most recent query submitted by session_id 66 and request_id 0:

SELECT * FROM sys.dm_exec_input_buffer (66,0);

  • Refer to the blocking_session_id column in sys.dm_exec_requests. When blocking_session_id = 0, a session isn't being blocked. While sys.dm_exec_requests lists only requests currently executing, any connection (active or not) is listed in sys.dm_exec_sessions. Build on this common join between sys.dm_exec_requests and sys.dm_exec_sessions in the next query.

  • Run this sample query to find the actively executing queries and their current SQL batch text or input buffer text, using the sys.dm_exec_sql_text or sys.dm_exec_input_buffer DMVs. If the data returned by the text field of sys.dm_exec_sql_text is NULL, the query isn't currently executing. In that case, the event_info field of sys.dm_exec_input_buffer contains the last command string passed to the SQL engine. This query can also be used to identify sessions blocking other sessions, including a list of session_ids blocked per session_id.

WITH cteBL (session_id, blocking_these) AS 
(SELECT s.session_id, blocking_these = x.blocking_these FROM sys.dm_exec_sessions s 
CROSS APPLY    (SELECT isnull(convert(varchar(6), er.session_id),'') + ', '  
                FROM sys.dm_exec_requests as er
                WHERE er.blocking_session_id = isnull(s.session_id ,0)
                AND er.blocking_session_id <> 0
                FOR XML PATH('') ) AS x (blocking_these)
)
SELECT s.session_id, blocked_by = r.blocking_session_id, bl.blocking_these
, batch_text = t.text, input_buffer = ib.event_info, * 
FROM sys.dm_exec_sessions s 
LEFT OUTER JOIN sys.dm_exec_requests r on r.session_id = s.session_id
INNER JOIN cteBL as bl on s.session_id = bl.session_id
OUTER APPLY sys.dm_exec_sql_text (r.sql_handle) t
OUTER APPLY sys.dm_exec_input_buffer(s.session_id, NULL) AS ib
WHERE blocking_these is not null or r.blocking_session_id > 0
ORDER BY len(bl.blocking_these) desc, r.blocking_session_id desc, r.session_id;
  • Run this more elaborate sample query, provided by Microsoft Support, to identify the head of a multiple session blocking chain, including the query text of the sessions involved in a blocking chain.
WITH cteHead ( session_id,request_id,wait_type,wait_resource,last_wait_type,is_user_process,request_cpu_time
,request_logical_reads,request_reads,request_writes,wait_time,blocking_session_id,memory_usage
,session_cpu_time,session_reads,session_writes,session_logical_reads
,percent_complete,est_completion_time,request_start_time,request_status,command
,plan_handle,sql_handle,statement_start_offset,statement_end_offset,most_recent_sql_handle
,session_status,group_id,query_hash,query_plan_hash) 
AS ( SELECT sess.session_id, req.request_id, LEFT (ISNULL (req.wait_type, ''), 50) AS 'wait_type'
    , LEFT (ISNULL (req.wait_resource, ''), 40) AS 'wait_resource', LEFT (req.last_wait_type, 50) AS 'last_wait_type'
    , sess.is_user_process, req.cpu_time AS 'request_cpu_time', req.logical_reads AS 'request_logical_reads'
    , req.reads AS 'request_reads', req.writes AS 'request_writes', req.wait_time, req.blocking_session_id,sess.memory_usage
    , sess.cpu_time AS 'session_cpu_time', sess.reads AS 'session_reads', sess.writes AS 'session_writes', sess.logical_reads AS 'session_logical_reads'
    , CONVERT (decimal(5,2), req.percent_complete) AS 'percent_complete', req.estimated_completion_time AS 'est_completion_time'
    , req.start_time AS 'request_start_time', LEFT (req.status, 15) AS 'request_status', req.command
    , req.plan_handle, req.[sql_handle], req.statement_start_offset, req.statement_end_offset, conn.most_recent_sql_handle
    , LEFT (sess.status, 15) AS 'session_status', sess.group_id, req.query_hash, req.query_plan_hash
    FROM sys.dm_exec_sessions AS sess
    LEFT OUTER JOIN sys.dm_exec_requests AS req ON sess.session_id = req.session_id
    LEFT OUTER JOIN sys.dm_exec_connections AS conn on conn.session_id = sess.session_id 
    )
, cteBlockingHierarchy (head_blocker_session_id, session_id, blocking_session_id, wait_type, wait_duration_ms,
wait_resource, statement_start_offset, statement_end_offset, plan_handle, sql_handle, most_recent_sql_handle, [Level])
AS ( SELECT head.session_id AS head_blocker_session_id, head.session_id AS session_id, head.blocking_session_id
    , head.wait_type, head.wait_time, head.wait_resource, head.statement_start_offset, head.statement_end_offset
    , head.plan_handle, head.sql_handle, head.most_recent_sql_handle, 0 AS [Level]
    FROM cteHead AS head
    WHERE (head.blocking_session_id IS NULL OR head.blocking_session_id = 0)
    AND head.session_id IN (SELECT DISTINCT blocking_session_id FROM cteHead WHERE blocking_session_id != 0)
    UNION ALL
    SELECT h.head_blocker_session_id, blocked.session_id, blocked.blocking_session_id, blocked.wait_type,
    blocked.wait_time, blocked.wait_resource, h.statement_start_offset, h.statement_end_offset,
    h.plan_handle, h.sql_handle, h.most_recent_sql_handle, [Level] + 1
    FROM cteHead AS blocked
    INNER JOIN cteBlockingHierarchy AS h ON h.session_id = blocked.blocking_session_id and h.session_id!=blocked.session_id --avoid infinite recursion for latch type of blocking
    WHERE h.wait_type COLLATE Latin1_General_BIN NOT IN ('EXCHANGE', 'CXPACKET') or h.wait_type is null
    )
SELECT bh.*, txt.text AS blocker_query_or_most_recent_query 
FROM cteBlockingHierarchy AS bh 
OUTER APPLY sys.dm_exec_sql_text (ISNULL ([sql_handle], most_recent_sql_handle)) AS txt;

SELECT [s_tst].[session_id],
[database_name] = DB_NAME (s_tdt.database_id),
[s_tdt].[database_transaction_begin_time], 
[sql_text] = [s_est].[text] 
FROM sys.dm_tran_database_transactions [s_tdt]
INNER JOIN sys.dm_tran_session_transactions [s_tst] ON [s_tst].[transaction_id] = [s_tdt].[transaction_id]
INNER JOIN sys.dm_exec_connections [s_ec] ON [s_ec].[session_id] = [s_tst].[session_id]
CROSS APPLY sys.dm_exec_sql_text ([s_ec].[most_recent_sql_handle]) AS [s_est];
  • Reference sys.dm_os_waiting_tasks that is at the thread/task layer of SQL. This returns information about what SQL wait type the request is currently experiencing. Like sys.dm_exec_requests, only active requests are returned by sys.dm_os_waiting_tasks.

Note

For much more on wait types including aggregated wait stats over time, see the DMV sys.dm_db_wait_stats. This DMV returns aggregate wait stats for the current database only.

  • Use the sys.dm_tran_locks DMV for more granular information on what locks have been placed by queries. This DMV can return large amounts of data on a production database, and is useful for diagnosing what locks are currently held.

Due to the INNER JOIN on sys.dm_os_waiting_tasks, the following query restricts the output from sys.dm_tran_locks only to currently blocked requests, their wait status, and their locks:

SELECT table_name = schema_name(o.schema_id) + '.' + o.name
, wt.wait_duration_ms, wt.wait_type, wt.blocking_session_id, wt.resource_description
, tm.resource_type, tm.request_status, tm.request_mode, tm.request_session_id
FROM sys.dm_tran_locks AS tm
INNER JOIN sys.dm_os_waiting_tasks as wt ON tm.lock_owner_address = wt.resource_address
LEFT OUTER JOIN sys.partitions AS p on p.hobt_id = tm.resource_associated_entity_id
LEFT OUTER JOIN sys.objects o on o.object_id = p.object_id or tm.resource_associated_entity_id = o.object_id
WHERE resource_database_id = DB_ID()
AND object_name(p.object_id) = '<table_name>';
  • With DMVs, storing the query results over time provides data points that allow you to review blocking over a specified time interval to identify persisted blocking or trends.

Gather information from Extended Events

In addition to the previous information, it's often necessary to capture a trace of the activities on the server to thoroughly investigate a blocking problem on Azure SQL Database. For example, if a session executes multiple statements within a transaction, only the last statement that was submitted is represented. However, one of the earlier statements might be the reason locks are still being held. A trace enables you to see all the commands executed by a session within the current transaction.

There are two ways to capture traces in SQL Server; Extended Events (XEvents) and Profiler Traces. However, SQL Server Profiler is deprecated trace technology not supported for Azure SQL Database. Extended Events is the newer tracing technology that allows more versatility and less effect on the observed system, and its interface is integrated into SQL Server Management Studio (SSMS).

Refer to the document that explains how to use the Extended Events New Session Wizard in SSMS. For Azure SQL databases however, SSMS provides an Extended Events subfolder under each database in Object Explorer. Use an Extended Events session wizard to capture these useful events:

  • Category Errors:

    • Attention
    • Error_reported
    • Execution_warning

  • Category Warnings:

    • Missing_join_predicate

  • Category Execution:

    • Rpc_completed
    • Rpc_starting
    • Sql_batch_completed
    • Sql_batch_starting

  • Category deadlock_monitor

    • database_xml_deadlock_report

  • Category session

    • Existing_connection
    • Login
    • Logout

Note

For detailed information on deadlocks, see Analyze and prevent deadlocks in Azure SQL Database and Fabric SQL database.

Identify and resolve common blocking scenarios

By examining the previous information, you can determine the cause of most blocking problems. The rest of this article is a discussion of how to use this information to identify and resolve some common blocking scenarios. This discussion assumes you have used the blocking scripts (referenced earlier) to capture information on the blocking SPIDs and have captured application activity using an XEvent session.

Analyze blocking data

  • Examine the output of the DMVs sys.dm_exec_requests and sys.dm_exec_sessions to determine the heads of the blocking chains, using blocking_these and session_id. This most clearly identifies which requests are blocked and which are blocking. Look further into the sessions that are blocked and blocking. Is there a common or root to the blocking chain? They likely share a common table, and one or more of the sessions involved in a blocking chain is performing a write operation.

  • Examine the output of the DMVs sys.dm_exec_requests and sys.dm_exec_sessions for information on the SPIDs at the head of the blocking chain. Look for the following fields:

    • sys.dm_exec_requests.status
      This column shows the status of a particular request. Typically, a sleeping status indicates that the SPID has completed execution and is waiting for the application to submit another query or batch. A runnable or running status indicates that the SPID is currently processing a query. The following table gives brief explanations of the various status values.
    Status Meaning
    Background The SPID is running a background task, such as deadlock detection, log writer, or checkpoint.
    Sleeping The SPID isn't currently executing. This usually indicates that the SPID is awaiting a command from the application.
    Running The SPID is currently running on a scheduler.
    Runnable The SPID is in the runnable queue of a scheduler and waiting to get scheduler time.
    Suspended The SPID is waiting for a resource, such as a lock or a latch.

    • sys.dm_exec_sessions.open_transaction_count
      This field tells you the number of open transactions in this session. If this value is greater than 0, the SPID is within an open transaction and might be holding locks acquired by any statement within the transaction.

    • sys.dm_exec_requests.open_transaction_count
      Similarly, this field tells you the number of open transactions in this request. If this value is greater than 0, the SPID is within an open transaction and might be holding locks acquired by any statement within the transaction.

    • sys.dm_exec_requests.wait_type, wait_time, and last_wait_type
      If the sys.dm_exec_requests.wait_type is NULL, the request isn't currently waiting for anything and the last_wait_type value indicates the last wait_type that the request encountered. For more information about sys.dm_os_wait_stats and a description of the most common wait types, see sys.dm_os_wait_stats. The wait_time value can be used to determine if the request is making progress. When a query against the sys.dm_exec_requests table returns a value in the wait_time column that is less than the wait_time value from a previous query of sys.dm_exec_requests, this indicates that the prior lock was acquired and released and is now waiting on a new lock (assuming nonzero wait_time). This can be verified by comparing the wait_resource between sys.dm_exec_requests output, which displays the resource for which the request is waiting.

    • sys.dm_exec_requests.wait_resource This field indicates the resource that a blocked request is waiting on. The following table lists common wait_resource formats and their meaning:

    Resource Format Example Explanation
    Table DatabaseID:ObjectID:IndexID TAB: 5:261575970:1 In this case, database ID 5 is the pubs sample database and object ID 261575970 is the titles table and 1 is the clustered index.
    Page DatabaseID:FileID:PageID PAGE: 5:1:104 In this case, database ID 5 is pubs, file ID 1 is the primary data file, and page 104 is a page belonging to the titles table. To identify the object_id the page belongs to, use the dynamic management function sys.dm_db_page_info, passing in the DatabaseID, FileId, PageId from the wait_resource.
    Key DatabaseID:Hobt_id (Hash value for index key) KEY: 5:72057594044284928 (3300a4f361aa) In this case, database ID 5 is pubs, and Hobt_ID 72057594044284928 corresponds to index_id 2 for object_id 261575970 (titles table). Use the sys.partitions catalog view to associate the hobt_id to a particular index_id and object_id. There's no way to unhash the index key hash to a specific key value.
    Row DatabaseID:FileID:PageID:Slot(row) RID: 5:1:104:3 In this case, database ID 5 is pubs, file ID 1 is the primary data file, page 104 is a page belonging to the titles table, and slot 3 indicates the row's position on the page.
    Compile DatabaseID:FileID:PageID:Slot(row) RID: 5:1:104:3 In this case, database ID 5 is pubs, file ID 1 is the primary data file, page 104 is a page belonging to the titles table, and slot 3 indicates the row's position on the page.
    • sys.dm_tran_active_transactions The sys.dm_tran_active_transactions DMV contains data about open transactions that can be joined to other DMVs for a complete picture of transactions awaiting commit or rollback. Use the following query to return information on open transactions, joined to other DMVs including sys.dm_tran_session_transactions. Consider a transaction's current state, transaction_begin_time, and other situational data to evaluate whether it could be a source of blocking.
    SELECT tst.session_id, [database_name] = db_name(s.database_id)
, tat.transaction_begin_time
, transaction_duration_s = datediff(s, tat.transaction_begin_time, sysdatetime()) 
, transaction_type = CASE tat.transaction_type  WHEN 1 THEN 'Read/write transaction'
                                                WHEN 2 THEN 'Read-only transaction'
                                                WHEN 3 THEN 'System transaction'
                                                WHEN 4 THEN 'Distributed transaction' END
, input_buffer = ib.event_info, tat.transaction_uow     
, transaction_state  = CASE tat.transaction_state    
            WHEN 0 THEN 'The transaction has not been completely initialized yet.'
            WHEN 1 THEN 'The transaction has been initialized but has not started.'
            WHEN 2 THEN 'The transaction is active - has not been committed or rolled back.'
            WHEN 3 THEN 'The transaction has ended. This is used for read-only transactions.'
            WHEN 4 THEN 'The commit process has been initiated on the distributed transaction.'
            WHEN 5 THEN 'The transaction is in a prepared state and waiting resolution.'
            WHEN 6 THEN 'The transaction has been committed.'
            WHEN 7 THEN 'The transaction is being rolled back.'
            WHEN 8 THEN 'The transaction has been rolled back.' END 
, transaction_name = tat.name, request_status = r.status
, azure_dtc_state = CASE tat.dtc_state 
                    WHEN 1 THEN 'ACTIVE'
                    WHEN 2 THEN 'PREPARED'
                    WHEN 3 THEN 'COMMITTED'
                    WHEN 4 THEN 'ABORTED'
                    WHEN 5 THEN 'RECOVERED' END
, tst.is_user_transaction, tst.is_local
, session_open_transaction_count = tst.open_transaction_count  
, s.host_name, s.program_name, s.client_interface_name, s.login_name, s.is_user_process
FROM sys.dm_tran_active_transactions tat 
INNER JOIN sys.dm_tran_session_transactions tst  on tat.transaction_id = tst.transaction_id
INNER JOIN sys.dm_exec_sessions s on s.session_id = tst.session_id 
LEFT OUTER JOIN sys.dm_exec_requests r on r.session_id = s.session_id
CROSS APPLY sys.dm_exec_input_buffer(s.session_id, null) AS ib;

    • Other columns

      The remaining columns in sys.dm_exec_sessions and sys.dm_exec_request can provide insight into the root of a problem as well. Their usefulness varies depending on the circumstances of the problem. For example, you can determine if the problem happens only from certain clients (hostname), on certain network libraries (net_library), when the last batch submitted by a SPID was last_request_start_time in sys.dm_exec_sessions, how long a request had been running using start_time in sys.dm_exec_requests, and so on.

Common blocking scenarios

The table below maps common symptoms to their probable causes.

The Waittype, Open_Tran, and Status columns refer to information returned by sys.dm_exec_request. Other columns might be returned by sys.dm_exec_sessions. The "Resolves?" column indicates whether or not the blocking resolves on its own, or whether the session should be killed via the KILL command. For more information, see KILL.

Scenario Waittype Open_Tran Status Resolves? Other Symptoms
1 NOT NULL >= 0 runnable Yes, when query finishes. In sys.dm_exec_sessions, reads, cpu_time, and/or memory_usage columns increase over time. Duration for the query is high when completed.
2 NULL >0 sleeping No, but SPID can be killed. An attention signal might be seen in the Extended Event session for this SPID, indicating a query time-out or cancel has occurred.
3 NULL >= 0 runnable No. Doesn't resolve until client fetches all rows or closes connection. SPID can be killed, but it can take up to 30 seconds. If open_transaction_count = 0, and the SPID holds locks while the transaction isolation level is default (READ COMMITTED), this is a likely cause.
4 Varies >= 0 runnable No. Doesn't resolve until client cancels queries or closes connections. SPIDs can be killed, but might take up to 30 seconds. The hostname column in sys.dm_exec_sessions for the SPID at the head of a blocking chain is the same as one of the SPID it's blocking.
5 NULL >0 rollback Yes. An attention signal might be seen in the Extended Events session for this SPID, indicating a query time-out or cancel has occurred, or simply a rollback statement has been issued.
6 NULL >0 sleeping Eventually. When Windows determines the session is no longer active, the Azure SQL Database connection is broken. The last_request_start_time value in sys.dm_exec_sessions is much earlier than the current time.

Detailed blocking scenarios

  1. Blocking caused by a normally running query with a long execution time

    Resolution: The solution to this type of blocking problem is to look for ways to optimize the query. Actually, this class of blocking problem can just be a performance problem, and require you to pursue it as such. For information on troubleshooting a specific slow-running query, see How to troubleshoot slow-running queries on SQL Server. For more information, see Monitor and Tune for Performance.

    Reports from the Query Store in SSMS are also a highly recommended and valuable tool for identifying the most costly queries, suboptimal execution plans. Also review Query Performance Insight.

    If the query performs only SELECT operations, consider running the statement under snapshot isolation if it's enabled in your database, especially if RCSI has been disabled. As when RCSI is enabled, queries reading data don't require shared (S) locks under snapshot isolation level. Additionally, snapshot isolation provides transaction level consistency for all statements in an explicit multi-statement transaction. Snapshot isolation might already be enabled in your database. Snapshot isolation might also be used with queries performing modifications, but you must handle update conflicts.

    If you have a long-running query that is blocking other users and can't be optimized, consider moving it from an OLTP environment to a dedicated reporting system, a synchronous read-only replica of the database.

  2. Blocking caused by a sleeping SPID that has an uncommitted transaction

    This type of blocking can often be identified by a SPID that is sleeping or awaiting a command, yet whose transaction nesting level (@@TRANCOUNT, open_transaction_count from sys.dm_exec_requests) is greater than zero. This can occur if the application experiences a query time-out, or issues a cancel without also issuing the required number of ROLLBACK and/or COMMIT statements. When a SPID receives a query time-out or a cancel, it terminates the current query and batch, but doesn't automatically roll back or commit the transaction. The application is responsible for this, as Azure SQL Database can't assume that an entire transaction must be rolled back due to a single query being canceled. The query time-out or cancel appears as an ATTENTION signal event for the SPID in the Extended Event session.

    To demonstrate an uncommitted explicit transaction, issue the following query:

    CREATE TABLE #test (col1 INT);
INSERT INTO #test SELECT 1;
BEGIN TRAN
UPDATE #test SET col1 = 2 where col1 = 1;

    Then, execute this query in the same window:

    SELECT @@TRANCOUNT;
ROLLBACK TRAN
DROP TABLE #test;

    The output of the second query indicates that the transaction nesting level is one. All the locks acquired in the transaction are still be held until the transaction was committed or rolled back. If applications explicitly open and commit transactions, a communication or other error could leave the session and its transaction in an open state.

    Use the script earlier in this article based on sys.dm_tran_active_transactions to identify currently uncommitted transactions across the instance.

    Resolutions:

    • Additionally, this class of blocking problem can also be a performance problem, and require you to pursue it as such. If the query execution time can be diminished, the query time-out or cancel wouldn't occur. It's important that the application is able to handle the time-out or cancel scenarios should they arise, but you might also benefit from examining the performance of the query.

    • Applications must properly manage transaction nesting levels, or they can cause a blocking problem following the cancellation of the query in this manner. Consider:

      • In the error handler of the client application, execute IF @@TRANCOUNT > 0 ROLLBACK TRAN following any error, even if the client application doesn't believe a transaction is open. Checking for open transactions is required, because a stored procedure called during the batch could have started a transaction without the client application's knowledge. Certain conditions, such as canceling the query, prevent the procedure from executing past the current statement, so even if the procedure has logic to check IF @@ERROR <> 0 and abort the transaction, this rollback code isn't executed in such cases.
      • If connection pooling is being used in an application that opens the connection and runs a few queries before releasing the connection back to the pool, such as a Web-based application, temporarily disabling connection pooling might help alleviate the problem until the client application is modified to handle the errors appropriately. By disabling connection pooling, releasing the connection causes a physical disconnect of the Azure SQL Database connection, resulting in the server rolling back any open transactions.
      • Use SET XACT_ABORT ON for the connection, or in any stored procedures that begin transactions and aren't cleaning up following an error. In the event of a run-time error, this setting aborts any open transactions and return control to the client. For more information, review SET XACT_ABORT.

    Note

    The connection is not reset until it is reused from the connection pool, so it is possible that a user could open a transaction and then release the connection to the connection pool, but it might not be reused for several seconds, during which time the transaction would remain open. If the connection is not reused, the transaction is aborted when the connection times out and is removed from the connection pool. Thus, it is optimal for the client application to abort transactions in their error handler or use SET XACT_ABORT ON to avoid this potential delay.

    Caution

    Following SET XACT_ABORT ON, T-SQL statements following a statement that causes an error aren't executed. This could affect the intended flow of existing code.

  3. Blocking caused by a SPID whose corresponding client application didn't fetch all result rows to completion

    After sending a query to the server, all applications must immediately fetch all result rows to completion. If an application doesn't fetch all result rows, locks can be left on the tables, blocking other users. If you're using an application that transparently submits SQL statements to the server, the application must fetch all result rows. If it doesn't (and if it can't be configured to do so), you might be unable to resolve the blocking problem. To avoid the problem, you can restrict poorly behaved applications to a reporting or a decision-support database, separate from the main OLTP database.

    The impact of this scenario is reduced when read committed snapshot is enabled on the database, which is the default configuration in Azure SQL Database. Learn more in the Understand blocking section of this article.

    Note

    See guidance for retry logic for applications connecting to Azure SQL Database.

    Resolution: The application must be rewritten to fetch all rows of the result to completion. This doesn't rule out the use of OFFSET and FETCH in the ORDER BY clause of a query to perform server-side paging.

  4. Blocking caused by a session in a rollback state

    A data modification query that is KILLed, or canceled outside of a user-defined transaction, is rolled back. This can also occur as a side effect of the client network session disconnecting, or when a request is selected as the deadlock victim. This can often be identified by observing the output of sys.dm_exec_requests, which might indicate the ROLLBACK command, and the percent_complete column might show progress.

    Thanks to Accelerated database recovery introduced in 2019, lengthy rollbacks should be rare.

    Resolution: Wait for the SPID to finish rolling back the changes that were made.

    To avoid this situation, don't perform large batch write operations or index creation or maintenance operations during busy hours on OLTP systems. If possible, perform such operations during periods of low activity.

  5. Blocking caused by an orphaned connection

    If the client application traps errors or the client workstation is restarted, the network session to the server might not be immediately canceled under some conditions. From the Azure SQL Database perspective, the client still appears to be present, and any locks acquired might still be retained. For more information, see How to troubleshoot orphaned connections in SQL Server.

    Resolution: If the client application has disconnected without appropriately cleaning up its resources, you can terminate the SPID by using the KILL command. The KILL command takes the SPID value as input. For example, to kill SPID 99, issue the following command:

    KILL 99

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