TiDB Node Error

Note:
This topic has been translated from a Chinese forum by GPT and might contain errors.

Original topic: tidb 节点报错

| username: rw12306

[TiDB Usage Environment] Production Environment / Testing / Poc
[TiDB Version] v6.1

After a large number of data insertions on the TiDB node, the data prompts the following information, causing the program to be unable to connect to the node directly.

| username: Kongdom | Original post link

Uh… the kernel reported an error directly~ Is it because the resources are exhausted?

| username: rw12306 | Original post link

This is running statistical metrics in batches. There are no programs running on the TiDB machine; only one TiDB node is deployed on this machine.

| username: Kongdom | Original post link

Take a look at the resource usage.

| username: rw12306 | Original post link

Is it through TiDB monitoring?

| username: rw12306 | Original post link

It’s already so high, how do we handle these?

| username: Kongdom | Original post link

This is calculated based on the number of cores. 1 core has a maximum of 100%, and 2 cores have a maximum of 200%.

| username: rw12306 | Original post link

First, I saw it go up to over 6000, and then the program connection was lost. Why is so much CPU being used, and it takes a long time to come down? Is there any optimization strategy for this?

| username: Kongdom | Original post link

How about slow queries?

| username: tidb狂热爱好者 | Original post link

Batch processing calculation Please provide slow SQL, usually in the dashboard.

| username: tidb狂热爱好者 | Original post link

Or first limit the timeout to 60 seconds and report an error if it exceeds that. Block the slowest SQL queries first.

| username: rw12306 | Original post link

This is the most time-consuming part here.

| username: rw12306 | Original post link

Each process is at 100%. How should this be handled? Or should the number of threads be reduced?

Logs

| username: alfred | Original post link

This error occurs when CPU, memory, and other resources are exhausted.