Snippet Name: Deadlock_Index_Recommendations
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Created Date: 2025-06-16 13:12:43
Last Modified Date: 2025-05-31 10:32:02
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Title: Deadlock Index Recommendations
Author: user
in AWS Aurura mySQL, i have this deadlock information in my logs. with this information, does it suggest an index that might prevent the same deadlock activity from occurring in the future?
Author: ChatGPT
Deadlock logs in AWS Aurora MySQL can provide valuable information about what caused the deadlock, and analyzing them can help identify whether adding or modifying an index would prevent future deadlocks. To determine if an index might help, follow these steps based on the information provided in the deadlock log:
### 1. **Analyze the Deadlock Information**
Look for the following details in the deadlock log:
- **Involved Queries**: Identify the SQL queries that were involved in the deadlock.
- **Tables**: Note the tables on which the deadlock occurred.
- **Indexes Used**: Review the indexes mentioned in the log and whether they were utilized effectively.
- **Lock Types**: Check the types of locks (e.g., S (shared), X (exclusive)) that were acquired and requested.
- **Wait Chain**: Understand the sequence of events leading to the deadlock.
### 2. **Understand the Root Cause**
Deadlocks typically occur when two transactions hold locks on resources that the other transaction needs. This can be due to:
- Inefficient index usage leading to a full table scan or range scans that lock more rows than necessary.
- Contention on the same rows or overlapping ranges due to inadequate indexing.
- Transaction logic that causes circular dependencies.
### 3. **Determine if an Index is Missing**
Use the deadlock log details to answer:
- Are the queries performing table scans or range scans where they could use an index to filter rows?
- Are the queries locking more rows than necessary due to insufficient indexing?
- Is there a pattern of contention on specific columns that suggests a
Author: user
------------------------
LATEST DETECTED DEADLOCK
------------------------
2024-11-22 16:47:17 23432261527296
*** (1) TRANSACTION:
TRANSACTION 304929143025280, ACTIVE 0 sec fetching rows
mysql tables in use 4, locked 4
LOCK WAIT 492 lock struct(s), heap size 57464, 989 row lock(s)
MySQL thread id 59945946, OS thread handle 23432813827840, query id 18104981302 10.30.0.182 _tm_app_prd System lock
CREATE TEMPORARY TABLE temp_customers_matched
SELECT t.id, t.hyperion_id, t.created, lower(t.contact_first_name) contact_first_name, lower(t.contact_last_name) contact_last_name,
t.contact_business_phone,
t.contact_cell_phone,
t.contact_home_phone,
t.contact_main_phone,
lower(t.contact_work_email) contact_work_email,
lower(t.contact_personal_email) contact_personal_email,
lower(t.contact_main_email) contact_main_email,
lower(t.vehicle_vin) vehicle_vin,
lower(t.vehicle_make) vehicle_make,
lower(t.vehicle_model) vehicle_model,
t.vehicle_year
FROM task_manager.task t
-- joining to lookup tasks only belongs to campaigns category
-- remove collation and deploy to INT
left join task_type_xref tref on t.task_type = tref.task_type
left join campaign_config cc on t
*** (1) HOLDS THE LOCK(S):
RECORD LOCKS space id 1987 page no 3165481 n bits 224 index composite01_idx of table `task_manager`.`task` trx id 304929143025280 lock mode S
Record lock, heap no 73 PHYSICAL RECORD: n_fields 5; compact format; info bits 0
0: len 7; hex 50415354445545; asc PASTDUE;;
1: len 4; hex 32343131; asc 2411;;
2: len 18; hex 4150504f494e544d454e545f325745454b53; asc APPOINTMENT_2WEEKS;;
3: len 5; hex 99b4e8bc61; asc a;;
4: len 16; hex b13fabeed50343e1aaca82f99c1546dc; asc ? C F ;;
Author: ChatGPT
To address the deadlock in this scenario and determine whether an index might help prevent it, let???s analyze the deadlock log and extract insights.
### Key Observations from the Log
1. **Query in Transaction (1):**
- The transaction involves a `CREATE TEMPORARY TABLE` statement, which selects data from `task_manager.task` and joins it with `task_type_xref` and `campaign_config`.
- The selection query likely involves filtering and aggregating rows before populating the temporary table.
2. **Lock Held:**
- The lock is on the `task_manager.task` table on the `composite01_idx` index, with a `Shared` (S) lock.
- This suggests the query is using this index during the read process.
3. **Lock Wait:**
- The transaction is waiting for locks while holding some locks. The locked index (`composite01_idx`) is used during the join and data filtering process.
4. **Concurrency:**
- The deadlock likely arises because another transaction is also trying to access the same rows or overlapping rows with a conflicting lock.
---
### Potential Causes
1. **Indexing:**
- The `composite01_idx` index is being used, but if it doesn???t efficiently filter rows, it may cause unnecessary row-level locking. This could lock more rows than needed, increasing the chances of contention.
2. **Join Logic:**
- The deadlock might be exacerbated by inefficient join operations or lack of appropriate indexes on the joined tables (`task_type_xref` and `campaign_config`).
3. **Transaction Design:**
- The query might not be accessing the rows in a consistent order across transactions, causing lock contention.
---
### Recommendations
#### 1. **Optimize Index Usage**
- **Evaluate `composite01_idx`:** Inspect the definition of this index. Ensure it includes the columns used in filtering and joining (e.g., `t.task_type`, `t.task_type_xref`, or other conditions in the query).
- **Covering Index:** If the query filters on specific columns in `task_manager.task`, consider creating a covering index to ensure efficient row filtering. For example:
```sql
CREATE INDEX idx_task_type_campaign ON task_manager.task (task_type, hyperion_id);
```
#### 2. **Indexes on Joined Tables**
- Check if the `task_type_xref` and `campaign_config` tables have appropriate indexes to support the `ON` conditions in the joins. Add indexes if they are missing, such as:
```sql
CREATE INDEX idx_task_type_xref ON task_type_xref (task_type);
CREATE INDEX idx_campaign_config ON campaign_config (<column used in join>);
```
#### 3. **Reduce Lock Contention**
- Ensure that the queries access rows in the same order across transactions to minimize conflicting locks.
- Consider using `SELECT ... FOR UPDATE` or a similar locking strategy to explicitly manage locks if appropriate.
#### 4. **Refactor the Query**
- Avoid using `CREATE TEMPORARY TABLE` in high-concurrency scenarios if possible. Instead, consider using a common table expression (CTE) or refactoring the logic to avoid intermediate table creation.
#### 5. **Partitioning or Sharding**
- If the `task_manager.task` table is very large, consider partitioning it by a relevant column (e.g., `task_type`) to reduce contention during reads.
---
### Actionable Next Steps
1. **Inspect Query Execution Plan:**
- Use `EXPLAIN` to check how MySQL is executing the query and identify areas where index usage can be optimized.
2. **Monitor and Tune:**
- Use the MySQL Performance Schema or Aurora Insights to monitor query performance and identify bottlenecks.
3. **Test Index Improvements:**
- Add and test new indexes in a staging environment to validate that they reduce lock contention and improve performance.
By following these steps, you can determine whether a specific index can help prevent future deadlocks and implement the changes with minimal disruption. Let me know if you'd like to delve into specific indexing strategies or need help analyzing an `EXPLAIN` plan!
Author: user
in that MySQL, i see that a stored procedure creates a temporary table. your suggestion was to chagne the Temporary table to common table expression. now i see the procedure is basically just doing a select statemnt. can i use transaction isolation level read uncommitted in mySQL?
Author: ChatGPT
Yes, you can use the `READ UNCOMMITTED` transaction isolation level in MySQL to minimize locking contention during reads. This isolation level allows a transaction to read data that has been modified by other transactions but not yet committed. It???s the least restrictive isolation level and can reduce locking overhead, making it suitable for scenarios where the data consistency requirements are low.
However, you need to carefully evaluate the trade-offs before applying this change. Here???s how you can implement it and the implications:
---
### 1. **How to Set Transaction Isolation Level to `READ UNCOMMITTED`**
You can change the isolation level within the scope of the stored procedure or a specific session to avoid affecting other transactions. Here???s an example:
```sql
DELIMITER $$
CREATE PROCEDURE GetCustomerData()
BEGIN
-- Set the transaction isolation level to READ UNCOMMITTED
SET TRANSACTION ISOLATION LEVEL READ UNCOMMITTED;
-- Perform the SELECT statement
SELECT
t.id,
t.hyperion_id,
t.created,
LOWER(t.contact_first_name) AS contact_first_name,
LOWER(t.contact_last_name) AS contact_last_name,
t.contact_business_phone,
t.contact_cell_phone,
t.contact_home_phone,
t.contact_main_phone,
LOWER(t.contact_work_email) AS contact_work_email,
LOWER(t.contact_personal_email) AS contact_personal_email,
LOWER(t.contact_main_email) AS contact_main_email,
LOWER(t.vehicle_vin) AS vehicle_vin,
LOWER(t.vehicle_make) AS vehicle_make,
LOWER(t.vehicle_model) AS vehicle_model,
t.vehicle_year
FROM
task_manager.task t
LEFT JOIN
task_type_xref tref ON t.task_type = tref.task_type
LEFT JOIN
campaign_config cc ON t.some_column = cc.some_column;
END$$
DELIMITER ;
```
You can invoke this stored procedure as usual. The isolation level will revert to the default (e.g., `REPEATABLE READ` or `READ COMMITTED`, depending on your MySQL settings) after the transaction or session ends.
---
### 2. **Implications of Using `READ UNCOMMITTED`**
#### Pros:
- **Reduced Lock Contention**: By allowing dirty reads, you avoid placing shared (S) locks on rows, reducing the chances of deadlocks and improving query concurrency.
- **Faster Reads**: Since the database skips acquiring certain locks and can read uncommitted changes, queries run faster.
#### Cons:
- **Dirty Reads**: You might read uncommitted changes from other transactions that could later be rolled back, resulting in inconsistent or invalid data.
- **Data Integrity Risks**: This isolation level might not be suitable for critical operations where consistency is important.
- **Limited Use Case**: Only use this level for operations where the data consistency isn't a priority or where you???re fine with potentially stale or dirty data.
---
### 3. **Best Practices**
1. **Scope Limitation**:
- Use `READ UNCOMMITTED` only in the stored procedure or session where it???s needed, rather than changing the global isolation level.
2. **Data Validity**:
- Evaluate whether temporary inconsistency in the data can impact your application or downstream processes.
3. **Monitor and Test**:
- Test the procedure in a staging environment under realistic concurrent workloads to ensure it behaves as expected without introducing issues.
4. **Alternatives**:
- If the purpose of the temporary table is merely to avoid locking, consider refactoring the query to use a Common Table Expression (CTE) as planned, instead of creating a temporary table.
---
### Example of Refactoring with a CTE
If the temporary table was being used to hold intermediate results, you can refactor it into a CTE:
```sql
WITH temp_customers_matched AS (
SELECT
t.id,
t.hyperion_id,
t.created,
LOWER(t.contact_first_name) AS contact_first_name,
LOWER(t.contact_last_name) AS contact_last_name,
t.contact_business_phone,
t.contact_cell_phone,
t.contact_home_phone,
t.contact_main_phone,
LOWER(t.contact_work_email) AS contact_work_email,
LOWER(t.contact_personal_email) AS contact_personal_email,
LOWER(t.contact_main_email) AS contact_main_email,
LOWER(t.vehicle_vin) AS vehicle_vin,
LOWER(t.vehicle_make) AS vehicle_make,
LOWER(t.vehicle_model) AS vehicle_model,
t.vehicle_year
FROM
task_manager.task t
LEFT JOIN
task_type_xref tref ON t.task_type = tref.task_type
LEFT JOIN
campaign_config cc ON t.some_column = cc.some_column
)
SELECT * FROM temp_customers_matched;
```
CTEs avoid the need for temporary tables and do not require additional locking, potentially reducing contention.
---
### Summary
- Yes, you can use `READ UNCOMMITTED` in MySQL for stored procedures, but you should ensure that the reduced consistency is acceptable for your use case.
- Refactoring to use a CTE instead of a temporary table is a cleaner and safer long-term solution, particularly in high-concurrency scenarios.
- Always test the impact of such changes in a controlled environment before deploying them to production.