What Does I/O Latencies and Bytes Mean in the Performance and sys Schemas?

The MEM InnoDB File I/O Graphs showing a peak in latency and bytes at 12:51.

The Performance Schema and sys schema are great for investigating what is going on in MySQL including investigating performance issues. In my work in MySQL Support, I have several times heard questions whether a peak in the InnoDB Data File I/O – Latency graph in MySQL Enterprise Monitor (MEM) or some values from the corresponding tables and view in the Performance Schema and sys schema are cause for concern. This blog will discuss what these observations means and how to use them.

The Tables and Views Involved

This blog will look into three sources in the Performance Schema for I/O latencies, so let’s first take a look at those tables. The three Performance Schema tables are:

  • events_waits_summary_global_by_event_name: with the event name set to wait/io/table/sql/handler or wait/io/file/%. This is the table used for the waits_global_by_latency and wait_classes_global_by_% views in the sys schema.
  • table_io_waits_summary_by_table: this is the table used for the schema_table_statistics% views in the sys schema.
  • file_summary_by_instance: this is the table used for the io_global_by_file_by% views in the sys schema.

These are also the sources used in MySQL Enterprise Monitor for the InnoDB Data File I/O graphs shown above. Let’s take a look at an example of each of the tables.


The events_waits_summary_global_by_event_name has aggregate data for wait events grouped by the event name. For the purpose of this discussion it is the table and file wait/io events that are of interested. An example of the data returned is:

mysql> SELECT *
         FROM performance_schema.events_waits_summary_global_by_event_name
        WHERE EVENT_NAME = 'wait/io/table/sql/handler'
              OR EVENT_NAME LIKE 'wait/io/file/%'
        LIMIT 5;
| wait/io/file/innodb/innodb_log_file  |    4003029 | 97371921796204 |        5371684 |       24324412 |   180878537324 |
| wait/io/table/sql/handler            |    4049559 | 43338753895440 |         494128 |       10702072 |   138756437188 |
| wait/io/file/innodb/innodb_data_file |      25850 | 11395061934996 |              0 |      440814508 |    43029060332 |
| wait/io/file/sql/binlog              |      20041 |  1316679917820 |              0 |       65699088 |    25816580304 |
| wait/io/file/sql/io_cache            |       2439 |    68212824648 |        1448920 |       27967360 |      628484180 |
5 rows in set (0.00 sec)

              sys.format_time(SUM_TIMER_WAIT) AS SumTimerWait,
              sys.format_time(MIN_TIMER_WAIT) AS MinTimeWait,
              sys.format_time(AVG_TIMER_WAIT) AS AvgTimerWait,
              sys.format_time(MAX_TIMER_WAIT) AS MaxTimerWait
         FROM performance_schema.events_waits_summary_global_by_event_name
        WHERE EVENT_NAME = 'wait/io/table/sql/handler'
              OR EVENT_NAME LIKE 'wait/io/file/
| EVENT_NAME                           | COUNT_STAR | SumTimerWait | MinTimeWait | AvgTimerWait | MaxTimerWait |
| wait/io/file/innodb/innodb_log_file  |    4003029 | 1.62 m       | 5.37 us     | 24.32 us     | 180.88 ms    |
| wait/io/table/sql/handler            |    4049559 | 43.34 s      | 494.13 ns   | 10.70 us     | 138.76 ms    |
| wait/io/file/innodb/innodb_data_file |      25853 | 11.40 s      | 0 ps        | 440.78 us    | 43.03 ms     |
| wait/io/file/sql/binlog              |      20041 | 1.32 s       | 0 ps        | 65.70 us     | 25.82 ms     |
| wait/io/file/sql/io_cache            |       2439 | 68.21 ms     | 1.45 us     | 27.97 us     | 628.48 us    |
5 rows in set (0.01 sec)

mysql> SELECT *
         FROM sys.waits_global_by_latency
        WHERE events = 'wait/io/table/sql/handler'
              OR events LIKE 'wait/io/file/%'
        LIMIT 5;
| events                               | total   | total_latency | avg_latency | max_latency |
| wait/io/file/innodb/innodb_log_file  | 4003029 | 1.62 m        | 24.32 us    | 180.88 ms   |
| wait/io/table/sql/handler            | 4049559 | 43.34 s       | 10.70 us    | 138.76 ms   |
| wait/io/file/innodb/innodb_data_file |   25874 | 11.43 s       | 441.88 us   | 43.03 ms    |
| wait/io/file/sql/binlog              |   20131 | 1.32 s        | 65.66 us    | 25.82 ms    |
| wait/io/file/sql/io_cache            |    2439 | 68.21 ms      | 27.97 us    | 628.48 us   |
5 rows in set (0.01 sec)

These three queries show the same data, just obtained and displayed in different ways.

In the result there are two groups of events. The wait/io/table events (the wait/io/table/sql/handler is the only event of this group which is why it can be listed explicitly) and the wait/io/file group.

The table events are for accessing data in tables. It does not matter whether the data is cached in the buffer pool or is accessed on disk. In this table and view, there is no distinguishing between different types of access (read, write, etc.).

The file events are, as the name suggest, for actually accessing files. There is one file event per file type. For example, in he output there are the wait/io/file/innodb/innodb_log_file event for accessing the InnoDB redo log files, the wait/io/file/innodb/innodb_data_file event for accessing the InnoDB data files themselves, the wait/io/file/sql/binlog event for the binary log files, etc.

In the second query, all of the timings are wrapped in the sys.format_time() function. The timings returned by the Performance Schema are in picoseconds (10^-12 second) which are somewhat hard for us humans to read. The sys.format_time() function converts the picoseconds to human readable strings. When you sort, however, make sure you sort by the original non-converted values.


Use the sys.format_time() function to convert the picoseconds to a human readable value, but do only so for the returned row; sort and filter by the original values. The Performance Schema always returns timings in picoseconds irrespective of the timer used internally for the event.

The sys schema by default returns the timing as human readable values. If you need the values in picoseconds prefix the table name with x$, for example sys.x$waits_global_by_latency. The sys schema includes an ORDER BY clause in most views. For the waits_global_by_latency view, the default ordering is by the total latency, so there is no need to add an ORDER BY clause in this example.


The table_io_waits_summary_by_table Performance Schema table and schema_table_statistics% sys schema views are related to the wait/io/table/sql/handler event just discussed. These provide information about the amount of time spent per table. Unlike querying the wait/io/table/sql/handler in the wait_events_% tables, it split the time spent into whether it is used for reads, writes, fetch, insert, update, or delete. The read and write columns are the aggregates for the corresponding read and write operations, respectively. Since fetch is the only read operation, the read and fetch columns will have the same values.

The table and view show the table I/O, i.e. the access to table data irrespective of whether the data is accessed in-memory or on disk. This is similar to the wait/io/table/sql/handler event. An example of the result of querying the table and view for the employees.salaries table is:

mysql> SELECT *
         FROM performance_schema.table_io_waits_summary_by_table
        WHERE OBJECT_SCHEMA = 'employees'
              AND OBJECT_NAME = 'salaries'\
*************************** 1. row ***************************
   OBJECT_SCHEMA: employees
     OBJECT_NAME: salaries
      COUNT_STAR: 2844047
  SUM_TIMER_WAIT: 31703741623644
  MIN_TIMER_WAIT: 4975456
  AVG_TIMER_WAIT: 11147072
  MAX_TIMER_WAIT: 138756437188
      COUNT_READ: 0
     COUNT_WRITE: 2844047
 SUM_TIMER_WRITE: 31703741623644
 AVG_TIMER_WRITE: 11147072
 MAX_TIMER_WRITE: 138756437188
    COUNT_INSERT: 2844047
SUM_TIMER_INSERT: 31703741623644
MAX_TIMER_INSERT: 138756437188
1 row in set (0.00 sec)

mysql> SELECT *
         FROM sys.schema_table_statistics
        WHERE table_schema = 'employees'
              AND table_name = 'salaries'\G
*************************** 1. row ***************************
     table_schema: employees
       table_name: salaries
    total_latency: 31.70 s
     rows_fetched: 0
    fetch_latency: 0 ps
    rows_inserted: 2844047
   insert_latency: 31.70 s
     rows_updated: 0
   update_latency: 0 ps
     rows_deleted: 0
   delete_latency: 0 ps
 io_read_requests: 493
          io_read: 7.70 MiB
  io_read_latency: 611.04 ms
io_write_requests: 8628
         io_write: 134.91 MiB
 io_write_latency: 243.19 ms
 io_misc_requests: 244
  io_misc_latency: 2.50 s
1 row in set (0.05 sec)

In this case it shows that there has been mostly writes – inserts – for the table. The sys schema view effectively joins on the performance_schema.file_summary_by_instance for the read columns, so for the schema_table_statistics view fetch and read are not synonyms.

So, what is it the file_summary_by_instance table shows that is different table the “table I/O” that has been the topic of the first two tables? Let’s see.


Unlike the two previous tables, the file_summary_by_instance shows how much time is spent on actual file I/O and how much data is accessed. This makes the file_summary_by_instance table and the corresponding sys schema views very useful for determining where time is spent doing disk I/O and which files have the most data accesses on disk.

An example of using the Performance Schema and two of the sys schema views is:

mysql> SELECT *
         FROM performance_schema.file_summary_by_instance
        WHERE FILE_NAME LIKE '%\\\\employees\\\\salaries.ibd'\G
*************************** 1. row ***************************
                FILE_NAME: C:\ProgramData\MySQL\MySQL Server 8.0\Data\employees\salaries.ibd
               EVENT_NAME: wait/io/file/innodb/innodb_data_file
    OBJECT_INSTANCE_BEGIN: 2230271392896
               COUNT_STAR: 9365
           SUM_TIMER_WAIT: 3351594917896
           MIN_TIMER_WAIT: 11970500
           AVG_TIMER_WAIT: 357885020
           MAX_TIMER_WAIT: 40146113948
               COUNT_READ: 493
           SUM_TIMER_READ: 611040652056
           MIN_TIMER_READ: 65421052
           AVG_TIMER_READ: 1239433224
           MAX_TIMER_READ: 16340582272
              COUNT_WRITE: 8628
          SUM_TIMER_WRITE: 243186542696
          MIN_TIMER_WRITE: 11970500
          AVG_TIMER_WRITE: 28185588
          MAX_TIMER_WRITE: 1984546920
               COUNT_MISC: 244
           SUM_TIMER_MISC: 2497367723144
           MIN_TIMER_MISC: 154910196
           AVG_TIMER_MISC: 10235113564
           MAX_TIMER_MISC: 40146113948
1 row in set (0.00 sec)

mysql> SELECT *
         FROM sys.io_global_by_file_by_latency
        WHERE file = '@@datadir\\employees\\salaries.ibd'\G
*************************** 1. row ***************************
         file: @@datadir\employees\salaries.ibd
        total: 9365
total_latency: 3.35 s
   count_read: 493
 read_latency: 611.04 ms
  count_write: 8628
write_latency: 243.19 ms
   count_misc: 244
 misc_latency: 2.50 s
1 row in set (0.09 sec)

mysql> SELECT *
         FROM sys.io_global_by_file_by_bytes
         WHERE file = '@@datadir\\employees\\salaries.ibd'\G
*************************** 1. row ***************************
         file: @@datadir\employees\salaries.ibd
   count_read: 493
   total_read: 7.70 MiB
     avg_read: 16.00 KiB
  count_write: 8628
total_written: 134.91 MiB
    avg_write: 16.01 KiB
        total: 142.61 MiB
    write_pct: 94.60
1 row in set (0.10 sec)

This example is from Microsoft Windows, and as always when backslashes are in play, it is fun to try to determine the appropriate number of backslashes to use. When specifying the file name with LIKE, you need four backslashes per backslash in the file name; when using = you need two backslashes.

Again, the values are split into reads and writes (though not as detailed as before with fetch, insert, update, and delete – that is not known at the level where the file I/O happens). The miscellaneous values include everything that is not considered reads or write; this includes opening and closing the file.

The sys schema queries not only have formatted the timings, but also the path and the bytes. This has been done using the sys.format_path() and sys.format_bytes() functions, respectively.

From the output, it can be seen that despite no rows were ever fetched (read) from the employees.salaries table (that was found in the previous output), there has still been some read file I/O. This was what the sys.schema_table_statistics view reflected.

So, what does all of this mean? The graph in MySQL Enterprise Monitor showed that there was six seconds file I/O latency for the InnoDB data files. Is that bad? As often with these kinds of questions, the answer is: “it depends”.

What to Make of the Values

In this case we have a case where the graphs in MySQL Enterprise Monitor show a peak for the latency and bytes used doing I/O on the InnoDB data files. This is actually disk I/O. But what exactly does that means and should the alarm sound?

Let’s first refresh our memory on how the graphs looks:

The MEM InnoDB File I/O Graphs showing a peak in latency and bytes at 12:31.

If you are not using MySQL Enterprise Monitor, you may have similar graphs from your monitoring solution, or you have obtained latency and bytes values from the tables and views discussed in this blog.

The latency graph shows that we have done six seconds if I/O. What does that mean? It is the aggregate I/O during the period the data was collected. In this case, the data is plotted for every minute, so in the one minute around 12:51, of the 60 seconds a total of six seconds was spent doing I/O. Now, the six seconds suddenly do no sound so bad. Similar for the bytes, around 4.6MiB of data was read or written.

In general, the values obtained either from the monitoring graphs or from the underlying tables cannot be used to conclude whether the is a problem or not. They just show how much I/O was done at different times.

Similar for the values from the Performance Schema. On their own they do not tell much. You can almost say they are too neutral – they just state how much work was done, not whether it was too much or too little.

A more useful way to use this data is in case a problem is reported. This can be that system administrator reports the disks are 100% utilized or that end users report the system is slow. Then, you can go and look at what happened. If the disk I/O was unusually high at that point in time, then that is likely related, and you can continue your investigation from there.

There are more reports in MySQL Enterprise Monitor both as time series graphs and as point-in-time snapshots. The point-in-time snapshots are often using the sys schema views but allows sorting. An example is the Database File I/O reports:

MEM's Database File I/O Report

MySQL Workbench also provides performance reports based on the sys scheme. The equivalent to the previous report is the Top File I/O Activity Report:

MySQL Workbench's Top File I/O Activity Report

The MySQL Workbench performance reports also allows you to export the report or copy the query used to generate the report, so you can execute it manually.

With respect to the wait/io/table/sql/handler events, then remember that I/O here does not mean disk I/O, but table I/O. So, all it means that time is accumulating for these events – including when looking at the per table is that the data in the table is used. There are also per index values in table_io_waits_summary_by_index_usage Performance Schema table and the schema_index_statistics sys view which have the same meaning. Whether a given usage is too high depends on many things. However, it can again be useful to investigate what is causing problems.

For the example data from this blog, it was triggered by loading the employees sample database. So, there was no problem. If you want to put data into your database, it must necessarily be written to the data file, otherwise it will not be persisted. However, if you think the data import took too long, you can use the data as part of your investigation on how to make the import faster.

The conclusion is that you should not panic if you see the I/O latencies peak. On their own they just mean that more work was done during that period that usual. Without context a peak is no worse than a dip (which could indicate something is preventing work from being done or that there is a natural slow period). Instead use the I/O latencies and bytes together with other observations to understand where MySQL is spending time and for which files data is being read and written.


I will recommend you look at the following references, if you want to understand more about the Performance Schema tables and sys schema views discussed in this blog:

The GitHub repository for the sys schema includes all the definitions of the views (and other objects). Since these are written in plain SQL, they are very useful to see in more depth where the data is coming from. The GitHub website allows you to browse through each of the files. Each sys schema object is defined in its own file.

I have worked with MySQL databases since 2006 both as an SQL developer, a database administrator, and for more than eight years as part of the Oracle MySQL Support team. I have spoken at MySQL Connect and Oracle OpenWorld on several occasions. I have contributed to the sys schema and four Oracle Certified Professional (OCP) exams for MySQL 5.6 to 8.0. I have written four books, all published at Apress.

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