Analyzing Amazon Aurora Slow Logs with pt-query-digest

Amazon Aurora MySQL slow query logs with pt-query-digest slow

Amazon Aurora MySQL slow query logs with pt-query-digest slowIn this blog post we shall discuss how you can analyze slow query logs from Amazon Aurora for MySQL, (referred to as Amazon Aurora in the remaining blog). The tools and techniques explained here apply to the other MySQL compatible services available under Amazon Aurora. However, we’ll focus specially on analyzing slow logs from Amazon Aurora version 2 (MySQL 5.7 compatible) using pt-query-digest. We believe there is a bug in Aurora where it logs really big numbers for query execution and lock times for otherwise really fast queries.

So, the main steps we need are:

  1. Enable slow query logging on your Amazon Aurora DB parameter group, apply the change when appropriate.
  2. Download the slow log(s) that match the time that you are interested to investigate, and optionally concatenate them.
  3. Run pt-query-digest on the downloaded logs and check the results.

Enable slow query logging

For our testing we decided to capture all the SELECT queries that were hitting our Amazon Aurora instance, mainly because we had a sysbench OLTP read only workload and that wouldn’t really have a lot of slow queries. An easy way to do so is to enable the capture of slow query logs and set long_query_time to 0 — you will need to enable slow query logging. To achieve that, we created a new DB parameter group and applied it to our test Aurora instance with the following three parameters set as below:


Once you have the above configuration applied to Amazon RDS, you will be able to see slow query logs being created in the Amazon RDS console.

Download the log file

You can download the log file of your choice using either the Amazon RDS console OR you can use the following AWS CLI command to achieve the same:

$ aws rds download-db-log-file-portion --db-instance-identifier perconasupport  --starting-token 0 --output text --log-file-name slowquery/mysql-slowquery.log.2018-09-03.09 > mysql-slowquery.log.2018-09-03.09

Depending on the size of the chosen log file, the above command will take some time to complete the download.

Run pt-query-digest on the log file

Once the file has been downloaded you can analyse that using the following pt-query-digest command.

$ pt-query-digest --group-by fingerprint --order-by Query_time:sum mysql-slowquery.log.2018-09-03.09

On our Aurora test slow log file, the initial results didn’t look right so we had to apply a workaround. Here is the header of the initial results from pt-query-digest:

# 456.2s user time, 2.5s system time, 43.80M rss, 141.48M vsz
# Current date: Tue Sep 4 15:54:21 2018
# Hostname: aahmed-GL503VD
# Files: mysql-slowquery.log.2018-09-03.09
# Overall: 5.13M total, 60 unique, 1.43k QPS, 507.43Gx concurrency _______
# Time range: 2018-09-03T08:00:04 to 2018-09-03T09:00:03
# Attribute total min max avg 95% stddev median
# ============ ======= ======= ======= ======= ======= ======= =======
# Exec time 1826227663297288s 1us 18446744073710s 355917782s 761us 80127878922s 93us
# Lock time 1401952549601936s 0 18446744073710s 273229812s 44us 70205933577s 23us
# Rows sent 94.71M 0 100 19.35 97.36 37.62 0.99
# Rows examine 216.26M 0 300 44.19 299.03 84.74 0.99
# Query size 196.24M 5 1.24k 40.08 72.65 18.90 36.69
# Profile
# Rank Query ID Response time Calls R/Call
# ==== ====================== =========================== ======= ========
# 1 0xE81D0B3DB4FB31BC5... 1346612317380813.0000 73.7% 3194111 421592210.5966 18... SELECT sbtest?
# 2 0x9934EF6887CC7A638... 147573952589685.0625 8.1% 319381 462062403.8051 18... SELECT sbtest?
# 3 0x8D589AFA4DFAEEED8... 110680464442264.1094 6.1% 319411 346514254.1812 18... BEGIN
# 4 0xFF7C69F51BBD3A736... 92233720368565.1875 5.1% 319388 288782673.0139 18... SELECT sbtest?
# 5 0xFFFCA4D67EA0A7888... 73786976294861.9844 4.0% 321238 229695665.8143 18... COMMIT
# MISC 0xMISC 55340232221335.8281 3.0% 657509 84166501.4796 0.0 <43 ITEMS>

What’s wrong with the above results is that the total query Exec time and Lock time are very large numbers. Digging deeper into the logs revealed a problem with the slow logs themselves that had very large numbers for Query time & Lock time for some queries. For instance in our case, of 5.13 million queries in the log file, only 111 had the anomaly. Even so, it was enough to skew the results.

# Time: 2018-09-03T08:41:47.363522Z
SELECT c FROM sbtest1 WHERE id=24278;
# Time: 2018-09-03T08:41:49.363224Z
# User@Host: perconasupport[perconasupport] @ [] Id: 20869
# Query_time: 18446744073709.550781 Lock_time: 18446744073709.550781 Rows_sent: 1 Rows_examined: 1
SET timestamp=1535964109;
SELECT c FROM sbtest2 WHERE id=989322;
# Time: 2018-09-03T08:41:49.363296Z
# Time: 2018-09-03T08:41:53.362947Z
# User@Host: perconasupport[perconasupport] @ [] Id: 20873
# Query_time: 18446744073709.550781 Lock_time: 18446744073709.550781 Rows_sent: 1 Rows_examined: 1
SET timestamp=1535964113;
SELECT c FROM sbtest1 WHERE id=246889;
# Time: 2018-09-03T08:41:53.363003Z

Incorrect logging

The above two queries are, in fact, really fast, but for some reason the execution time & lock times are wrongly logged in the slow query log. Since the number of such query log records is statistically negligible compared to the total number of queries, we decided to ask pt-query-digest to ignore them using the command line parameter –attribute-value-limit . The default value of this parameter is 0. We decided to increase that to 2^32, and make it ignore the large numbers from the slow query log. So, the pt-query-digest command became:

$ pt-query-digest --group-by fingerprint --order-by Query_time:sum --attribute-value-limit=4294967296 mysql-slowquery.log.2018-09-03.09

This caused the 111 queries with the bad log times to be ignored and the results looked good. In our case, the ignored queries were bad variants of queries for which good versions existed. You can tell this because the number of unique queries remained the same as before after the bad variants were ignored. However, this may not always hold true and one should expect to lose some fidelity, especially if you are analyzing a smaller slow log.

# 441s user time, 450ms system time, 38.19M rss, 111.76M vsz
# Current date: Tue Sep 4 16:23:33 2018
# Hostname: aahmed-GL503VD
# Files: mysql-slowquery.log.2018-09-03.09
# Overall: 5.13M total, 60 unique, 1.43k QPS, 0.30x concurrency __________
# Time range: 2018-09-03T08:00:04 to 2018-09-03T09:00:03
# Attribute total min max avg 95% stddev median
# ============ ======= ======= ======= ======= ======= ======= =======
# Exec time 1096s 1us 198ms 213us 761us 431us 93us
# Lock time 180s 0 103ms 34us 44us 161us 23us
# Rows sent 94.71M 0 100 19.35 97.36 37.62 0.99
# Rows examine 216.26M 0 300 44.19 299.03 84.74 0.99
# Query size 196.24M 5 1.24k 40.08 72.65 18.90 36.69
# Profile
# Rank Query ID Response time Calls R/Call V/M Ite
# ==== =========================== ============== ======= ====== ===== ===
# 1 0xE81D0B3DB4FB31BC558CAE... 400.1469 36.5% 3194111 0.0001 0.00 SELECT sbtest?
# 2 0xF0C5AE75A52E847D737F39... 161.4065 14.7% 319453 0.0005 0.00 SELECT sbtest?
# 3 0xFFFCA4D67EA0A788813031... 155.8740 14.2% 321238 0.0005 0.00 COMMIT
# 4 0x8D589AFA4DFAEEED85FFF5... 107.9827 9.9% 319411 0.0003 0.00 BEGIN
# 5 0x9934EF6887CC7A6384D1DE... 94.1002 8.6% 319381 0.0003 0.00 SELECT sbtest?
# 6 0xFF7C69F51BBD3A736EEB1B... 79.9279 7.3% 319388 0.0003 0.00 SELECT sbtest?
# 7 0xA729E7889F57828D3821AE... 75.3969 6.9% 319398 0.0002 0.00 SELECT sbtest?
# MISC 0xMISC 21.1212 1.9% 18658 0.0011 0.0 <41 ITEMS>
# Query 1: 1.27k QPS, 0.16x concurrency, ID 0xE81D0B3DB4FB31BC558CAEF5F387E929 at byte 358647353
# Scores: V/M = 0.00
# Time range: 2018-09-03T08:00:04 to 2018-09-03T08:42:00
# Attribute pct total min max avg 95% stddev median
# ============ === ======= ======= ======= ======= ======= ======= =======
# Count 62 3194111
# Exec time 36 400s 10us 198ms 125us 332us 300us 80us
# Lock time 74 134s 0 26ms 42us 49us 154us 27us
# Rows sent 3 3.01M 0 1 0.99 0.99 0.11 0.99
# Rows examine 1 3.01M 0 1 0.99 0.99 0.11 0.99
# Query size 57 112.37M 32 38 36.89 36.69 0.53 36.69
# String:
# Databases perconasupport
# Hosts
# Users perconasupport
# Query_time distribution
# 1us
# 10us ################################################################
# 100us ##############
# 1ms #
# 10ms #
# 100ms #
# 1s

That number looks familiar

The really big number 18446744073709.550781 seemed to ring a bell. A quick web search revealed that it could be a regression of an old bug in MySQL’s code. The following bugs were found to have the same value being reported for query exec time & query lock time.

Once slow logs were enabled, we used this sysbench command  to generate the workload for the Amazon Aurora instance. You might like to try it yourselves. Please note that this used sysbench version 1.0.14.
$ sysbench --db-driver=mysql --mysql-user=perconasupport --mysql-password=XXXXXXX  --mysql-db=perconasupport --range_size=100 --table_size=1000000 --tables=2 --threads=6 --events=0 --time=600 --rand-type=uniform /usr/share/sysbench/oltp_read_only.lua run

If you are an Amazon Aurora user, have you found any problems analyzing slow query logs? You are welcome to use the comments section, below, to let me know.

Percona Toolkit

pt-query-digest is part of Percona Toolkit, a collection of advanced open source command-line tools, developed and used by the Percona technical staff. Percona Toolkit is open source and free to download and use.

The post Analyzing Amazon Aurora Slow Logs with pt-query-digest appeared first on Percona Database Performance Blog.


New PERFORMANCE_SCHEMA defaults in MySQL 5.7.7

I thought it was worth a moment to reiterate on the new Performance Schema related defaults that MySQL 5.7.7 brings to the table, for various reasons.

For one, most of you might have noticed that profiling was marked as deprecated in MySQL 5.6.7. So it is expected that you invest into learning more about Performance Schema (and Mark’s sys schema!).

Second, there are lots of virtual environments and appliances out there running Community Edition MySQL where Performance Schema can be a useful tool for analyzing performance. Thus, expect to see more articles about using PERFORMANCE_SCHEMA and SYS_SCHEMA from us!

Third, we have more and more junior readers who might benefit from light reads such as this. :)

The new defaults that I wanted to highlight are mentioned in the MySQL 5.7.7 release notes:
– The MySQL sys schema is now installed by default during data directory installation.
– The events_statements_history and events_transactions_history consumers now are enabled by default.

Note that if you are upgrading from an earlier version of MySQL to 5.7.7 to get these goodies you will need to run mysql_upgrade and restart the database for the above changes to take effect.

So what do these mean?

If you haven’t had a chance to dig into PERFORMANCE_SCHEMA, check out the quick start guide here. PERFORMANCE_SCHEMA is a nify tool (implemented as a union of a storage engine and a schema in MySQL) to monitor MySQL server execution at a low level, with a focus on performance metrics. It monitors for events that have been “instrumented”, such as function calls, OS wait times, synchronization calls, etc. With performance nomenclature “instruments” are essentially “probes”. The events that the instruments generate can be processed by consumers. Note that not all instruments or consumers are enabled by default.

Some would say that the structure of PERFORMANCE_SCHEMA may be complex and may not be very DBA-friendly. This is what led to the birth of SYS_SCHEMA. For those who are not familiar with Mark Leith’s SYS_SCHEMA and prefer TL;DR – it provides human friendly views, functions and procedures that can help you analyze database usage using PERFORMANCE_SCHEMA. If you haven’t had a chance to check it out yet you might want to read Miguel’s article on using the sys schema or Alexander Rubin’s article about using it in multitenant environments and give it a spin!

I welcome the fact that events_statements_history and events_transactions_history consumers are enabled by default in MySQL 5.7.7 as it means that we get some handy performance details available to us out of the box in vanilla MySQL. Note that these are per-thread tables and by default the history length (the length of the number of entries present; more on those variables here) is automatically sized, thus you may need to increase them.

What details do you get off the bat with them?

Consider the following example:

mysql> select * from performance_schema.events_statements_history where event_id=353G
*************************** 1. row ***************************
              THREAD_ID: 20
               EVENT_ID: 353
           END_EVENT_ID: 456
             EVENT_NAME: statement/sql/select
            TIMER_START: 1818042501405000
              TIMER_END: 1818043715449000
             TIMER_WAIT: 1214044000
              LOCK_TIME: 67000000
               SQL_TEXT: select * from imdb.title limit 100
                 DIGEST: ec93c38ab021107c2160259ddee31faa
            DIGEST_TEXT: SELECT * FROM `imdb` . `title` LIMIT ?
         CURRENT_SCHEMA: performance_schema
            OBJECT_TYPE: NULL
            OBJECT_NAME: NULL
            MYSQL_ERRNO: 0
                 ERRORS: 0
               WARNINGS: 0
          ROWS_AFFECTED: 0
              ROWS_SENT: 100
          ROWS_EXAMINED: 100
           SELECT_RANGE: 0
            SELECT_SCAN: 1
             SORT_RANGE: 0
              SORT_ROWS: 0
              SORT_SCAN: 0
          NO_INDEX_USED: 1
1 row in set (0.00 sec)

As you can see from above you get similar data that you are used to seeing from EXPLAINs and slow query logs, such as query run time, locking time, rows sent/examined, etc. For instance, in above output my query obtained about a 100 rows (lines 26-27), avoided creating temp tables (lines 28-29) and didn’t have to sort (lines 36-38) and no index was used (line 39) and it ran for about 121 ms (TIMER_END-TIMER_START). The list of details provided is not as abundant as it could be but I imagine that with newer releases the list may grow.

If you want to read on and are curious about how to use Performance Schema for profiling check out Jervin’s great article here!

The post New PERFORMANCE_SCHEMA defaults in MySQL 5.7.7 appeared first on MySQL Performance Blog.

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