1. What is a dead lock
A deadlock refers to a blocking state in which two or more transactions are waiting for resources held by each other, causing none of these transactions to continue execution. In short, transaction A waits for transaction B to release resources, and transaction B is waiting for transaction A to release resources, thus forming a closed waiting ring.
In PostgreSQL, deadlocks usually occur when multiple concurrent transactions try to acquire and hold the lock in an inconsistent order.
2. Symptoms of deadlock
When a deadlock occurs, some of the following symptoms may be observed:
- Some transactions are waiting for a long time without any progress.
- The application response becomes slow and even a timeout error occurs.
- The performance metrics of the database (such as throughput, latency, etc.) have dropped significantly.
3. Diagnosing deadlock
1. View the database log
PostgreSQL records deadlock-related information in its log files. By default, the details of the deadlock will be recorded inin the file. You can search for deadlock-related log entries through the following keywords:
DETAIL: Process <pid1> waits for ShareLock on transaction <txid1>; blocked by process <pid2>. Process <pid2> waits for ShareLock on transaction <txid2>; blocked by process <pid1>.
The above log fragment shows two processes (pid1andpid2) blocks each other, forming a deadlock.
2. Use the system view
PostgreSQL provides some system views that can be used to obtain information about currently running transactions and locks to help diagnose deadlock problems.
pg_stat_activity: This view provides information about the currently active backend process, including the status of the query being executed and the transaction.
SELECT * FROM pg_stat_activity;
By viewingstatecolumns can determine the status of the transaction, such asactive(Activity),idle in transaction(Idle in the transaction),blocked(blocking), etc.
pg_locks: This view shows information about the currently acquired lock.
SELECT * FROM pg_locks;
Can be linkedpg_stat_activityandpg_locksView to obtain more detailed deadlock-related information.
3. Enable tracking for deadlock detection
It can be modifiedParameters in the configuration file to enable more detailed deadlock detection tracking.
log_lock_waits = on deadlock_timeout = 1s
4. Solve the deadlock
1. Optimize transaction logic
The most fundamental solution is to optimize transaction logic in your application to avoid conditions that may lead to deadlocks. For example:
- Make sure to get resources in the same order. If multiple transactions need to access table A and table B, let them all proceed in the order of accessing table A first and then accessing table B.
Here is an example of a situation where incorrect resource acquisition order can lead to deadlocks:
Transaction 1:
BEGIN; -- Get the table A Exclusive lock LOCK TABLE A IN EXCLUSIVE MODE; -- Do some operations here -- Pause for a while，Simulate other operations SELECT pg_sleep(5); -- 尝试Get the table B Exclusive lock LOCK TABLE B IN EXCLUSIVE MODE; COMMIT;
Transaction 2:
BEGIN; -- Get the table B Exclusive lock LOCK TABLE B IN EXCLUSIVE MODE; -- Do some operations here -- Pause for a while，Simulate other operations SELECT pg_sleep(5); -- 尝试Get the table A Exclusive lock LOCK TABLE A IN EXCLUSIVE MODE; COMMIT;
In the above example, transaction 1 first acquires the lock of table A and then pauses for a while before acquiring the lock of table B. At the same time, transaction 2 first acquires the lock of table B, and then pauses for a while before acquiring the lock of table A. This can lead to a deadlock because transaction 1 waits for transaction 2 to release the lock of table B, while transaction 2 waits for transaction 1 to release the lock of table A.
The correct way to do this is to have both transactions acquire the locks of table A and table B in the same order, for example:
Transaction 1:
BEGIN; -- Get the table A Exclusive lock LOCK TABLE A IN EXCLUSIVE MODE; -- Get the table B Exclusive lock LOCK TABLE B IN EXCLUSIVE MODE; COMMIT;
Transaction 2:
BEGIN; -- Get the table A Exclusive lock LOCK TABLE A IN EXCLUSIVE MODE; -- Get the table B Exclusive lock LOCK TABLE B IN EXCLUSIVE MODE; COMMIT;
- Minimize the time the transaction holds locks. Decompose long-running transactions into smaller sub-transactions, and submit sub-transactions that do not require long-term locking of resources.
For example, if there is a complex computation and data update process, it can be divided into multiple steps, and the transaction is committed after each step is completed:
BEGIN; -- step 1：Data reading and calculation SELECT * FROM some_table WHERE some_condition; -- Submit transactions COMMIT; BEGIN; -- step 2：基于step 1 Update the results of data UPDATE some_table SET some_column = some_value WHERE some_other_condition; COMMIT;
- Avoid using unnecessary locks in transactions. Acquire locks only when resources really need to be locked to ensure data consistency.
2. Retry mechanism
When a deadlock is detected, a retry mechanism can be implemented in the application. That is, when a transaction fails due to a deadlock, the transaction will be automatically re-execute.
The following is a using Python andpsycopg2Sample code for library implementation of retry mechanism:
import psycopg2
import time
import random
def execute_transaction(conn, query):
max_retries = 5
retry_delay = 1 # Initial retry delay time (seconds)
for retry in range(max_retries):
try:
with () as cur:
(query)
()
return # Execute successfully, exit the function except as e:
()
if "deadlock detected" in str(e):
if retry < max_retries - 1:
delay = retry_delay * (2 ** retry) + (0, 1000) / 1000
print(f"Deadlock occurs，Try again {retry + 1} Second-rate，wait {delay} Second...")
(delay)
retry_delay *= 2
else:
raise e # Maximum retry times are reached and an exception is thrown else:
raise e # Other errors, throw exception
# Example usageconn = (database="your_database", user="your_user", password="your_password", host="your_host", port="your_port")
query = "your_transaction_query"
execute_transaction(conn, query)
In the above code, aexecute_transactionfunction, which attempts to execute a given transaction query. If you encounter a deadlock error, you will try again, and the waiting time for each retry gradually increases (byretry_delaycalculate) to avoid frequent retry putting too much pressure on the system. If the maximum number of retrys is reached and the deadlock is still encountered, an exception is thrown.
3. Increase lock timeout
The probability of deadlock can be reduced by setting the lock timeout time when connecting to the database. But this is just a temporary solution and may mask the real problem.
conn = (database="your_database", user="your_user", password="your_password", host="your_host", port="your_port", options="-c lock_timeout=5000")
In the above connection string, set the lock timeout to 5000 milliseconds.
5. Best practices for preventing deadlocks
1. Design a reasonable database architecture
A reasonable database table structure and index design can reduce competition and conflict of locks. Ensure the correct use of the index and avoid unnecessary full table scanning.
2. Control concurrent access
The degree of concurrent access is reasonably controlled according to the actual needs of the application. Concurrent operations can be coordinated using queues, thread pools and other technologies.
3. Regular monitoring and analysis
Regularly check the database performance indicators, lock usage, and transaction execution time to promptly discover potential deadlock problems.
6. Summary
Deadlocks are a complex problem that can arise in PostgreSQL databases, but with the right diagnostic methods and appropriate solutions, the occurrence of deadlocks can be effectively solved and prevented. The key is to understand transaction logic, optimize resource access order, control lock holding time, and adopt reasonable retry mechanisms and monitoring strategies.
By continuously optimizing application and database design and timely handling deadlock problems, we can ensure the stable and efficient operation of PostgreSQL databases, providing reliable support for applications.
The above is a detailed explanation of how to diagnose and solve the deadlock problem in PostgreSQL. For more information about PostgreSQL deadlock problem, please follow my other related articles!