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@@ -1227,7 +1227,7 @@
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@@ -1298,8 +1298,8 @@
<p><a href="https://stackify.com/what-are-crud-operations/">CRUD operations</a> - create, read, update, delete queries</p>
<p>Management operations - create DBs/tables/indexes etc, backup, import/export, users, access controls</p>
<p>Exercise: Classify the below queries into the four types - DDL (definition), DML(manipulation), DCL(control) and TCL(transactions) and explain in detail.</p>
<pre><code>insert, create, drop, delete, update, commit, rollback, truncate, alter, grant, revoke
</code></pre>
<div class="highlight"><pre><span></span><code>insert, create, drop, delete, update, commit, rollback, truncate, alter, grant, revoke
</code></pre></div>
<p>You can practise these in the <a href="https://linkedin.github.io/school-of-sre/databases_sql/lab/">lab section</a>.</p>
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@@ -10,7 +10,7 @@
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@@ -1266,7 +1266,7 @@
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@@ -10,7 +10,7 @@
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@@ -1207,7 +1207,7 @@
<p><strong>Setup</strong></p>
<p>Create a working directory named sos or something similar, and cd into it.</p>
<p>Enter the following into a file named my.cnf under a directory named custom.</p>
<pre><code>sos $ cat custom/my.cnf
<div class="highlight"><pre><span></span><code>sos $ cat custom/my.cnf
[mysqld]
# These settings apply to MySQL server
# You can set port, socket path, buffer size etc.
@@ -1215,76 +1215,76 @@
slow_query_log=1
slow_query_log_file=/var/log/mysqlslow.log
long_query_time=0.1
</code></pre>
</code></pre></div>
<p>Start a container and enable slow query log with the following:</p>
<pre><code>sos $ docker run --name db -v custom:/etc/mysql/conf.d -e MYSQL_ROOT_PASSWORD=realsecret -d mysql:8
sos $ docker cp custom/mysqld.cnf $(docker ps -qf &quot;name=db&quot;):/etc/mysql/conf.d/custom.cnf
sos $ docker restart $(docker ps -qf &quot;name=db&quot;)
</code></pre>
<div class="highlight"><pre><span></span><code>sos $ docker run --name db -v custom:/etc/mysql/conf.d -e <span class="nv">MYSQL_ROOT_PASSWORD</span><span class="o">=</span>realsecret -d mysql:8
sos $ docker cp custom/mysqld.cnf <span class="k">$(</span>docker ps -qf <span class="s2">&quot;name=db&quot;</span><span class="k">)</span>:/etc/mysql/conf.d/custom.cnf
sos $ docker restart <span class="k">$(</span>docker ps -qf <span class="s2">&quot;name=db&quot;</span><span class="k">)</span>
</code></pre></div>
<p>Import a sample database</p>
<pre><code>sos $ git clone git@github.com:datacharmer/test_db.git
sos $ docker cp test_db $(docker ps -qf &quot;name=db&quot;):/home/test_db/
sos $ docker exec -it $(docker ps -qf &quot;name=db&quot;) bash
root@3ab5b18b0c7d:/# cd /home/test_db/
<div class="highlight"><pre><span></span><code>sos $ git clone git@github.com:datacharmer/test_db.git
sos $ docker cp test_db <span class="k">$(</span>docker ps -qf <span class="s2">&quot;name=db&quot;</span><span class="k">)</span>:/home/test_db/
sos $ docker <span class="nb">exec</span> -it <span class="k">$(</span>docker ps -qf <span class="s2">&quot;name=db&quot;</span><span class="k">)</span> bash
root@3ab5b18b0c7d:/# <span class="nb">cd</span> /home/test_db/
root@3ab5b18b0c7d:/# mysql -uroot -prealsecret mysql &lt; employees.sql
root@3ab5b18b0c7d:/etc# touch /var/log/mysqlslow.log
root@3ab5b18b0c7d:/etc# chown mysql:mysql /var/log/mysqlslow.log
</code></pre>
</code></pre></div>
<p><em>Workshop 1: Run some sample queries</em>
Run the following</p>
<pre><code>$ mysql -uroot -prealsecret mysql
Run the following
<div class="highlight"><pre><span></span><code>$ mysql -uroot -prealsecret mysql
mysql&gt;
# inspect DBs and tables
# the last 4 are MySQL internal DBs
<span class="c1"># inspect DBs and tables</span>
<span class="c1"># the last 4 are MySQL internal DBs</span>
mysql&gt; show databases;
mysql&gt; show databases<span class="p">;</span>
+--------------------+
| Database |
<span class="p">|</span> Database <span class="p">|</span>
+--------------------+
| employees |
| information_schema |
| mysql |
| performance_schema |
| sys |
<span class="p">|</span> employees <span class="p">|</span>
<span class="p">|</span> information_schema <span class="p">|</span>
<span class="p">|</span> mysql <span class="p">|</span>
<span class="p">|</span> performance_schema <span class="p">|</span>
<span class="p">|</span> sys <span class="p">|</span>
+--------------------+
&gt; use employees;
mysql&gt; show tables;
&gt; use employees<span class="p">;</span>
mysql&gt; show tables<span class="p">;</span>
+----------------------+
| Tables_in_employees |
<span class="p">|</span> Tables_in_employees <span class="p">|</span>
+----------------------+
| current_dept_emp |
| departments |
| dept_emp |
| dept_emp_latest_date |
| dept_manager |
| employees |
| salaries |
| titles |
<span class="p">|</span> current_dept_emp <span class="p">|</span>
<span class="p">|</span> departments <span class="p">|</span>
<span class="p">|</span> dept_emp <span class="p">|</span>
<span class="p">|</span> dept_emp_latest_date <span class="p">|</span>
<span class="p">|</span> dept_manager <span class="p">|</span>
<span class="p">|</span> employees <span class="p">|</span>
<span class="p">|</span> salaries <span class="p">|</span>
<span class="p">|</span> titles <span class="p">|</span>
+----------------------+
# read a few rows
mysql&gt; select * from employees limit 5;
<span class="c1"># read a few rows</span>
mysql&gt; <span class="k">select</span> * from employees limit <span class="m">5</span><span class="p">;</span>
# filter data by conditions
mysql&gt; select count(*) from employees where gender = 'M' limit 5;
<span class="c1"># filter data by conditions</span>
mysql&gt; <span class="k">select</span> count<span class="o">(</span>*<span class="o">)</span> from employees where <span class="nv">gender</span> <span class="o">=</span> <span class="s1">&#39;M&#39;</span> limit <span class="m">5</span><span class="p">;</span>
# find count of particular data
mysql&gt; select count(*) from employees where first_name = 'Sachin';
</code></pre>
<p><em>Workshop 2: Use explain and explain analyze to profile a query, identify and add indexes required for improving performance</em></p>
<pre><code># View all indexes on table
#(\G is to output horizontally, replace it with a ; to get table output)
mysql&gt; show index from employees from employees\G
*************************** 1. row ***************************
<span class="c1"># find count of particular data</span>
mysql&gt; <span class="k">select</span> count<span class="o">(</span>*<span class="o">)</span> from employees where <span class="nv">first_name</span> <span class="o">=</span> <span class="s1">&#39;Sachin&#39;</span><span class="p">;</span>
</code></pre></div></p>
<p><em>Workshop 2: Use explain and explain analyze to profile a query, identify and add indexes required for improving performance</em>
<div class="highlight"><pre><span></span><code><span class="c1"># View all indexes on table </span>
<span class="c1">#(\G is to output horizontally, replace it with a ; to get table output)</span>
mysql&gt; show index from employees from employees<span class="se">\G</span>
*************************** <span class="m">1</span>. row ***************************
Table: employees
Non_unique: 0
Non_unique: <span class="m">0</span>
Key_name: PRIMARY
Seq_in_index: 1
Seq_in_index: <span class="m">1</span>
Column_name: emp_no
Collation: A
Cardinality: 299113
Cardinality: <span class="m">299113</span>
Sub_part: NULL
Packed: NULL
Null:
@@ -1294,28 +1294,28 @@ Index_comment:
Visible: YES
Expression: NULL
# This query uses an index, idenitfied by 'key' field
# By prefixing explain keyword to the command,
# we get query plan (including key used)
mysql&gt; explain select * from employees where emp_no &lt; 10005\G
*************************** 1. row ***************************
id: 1
<span class="c1"># This query uses an index, idenitfied by &#39;key&#39; field</span>
<span class="c1"># By prefixing explain keyword to the command, </span>
<span class="c1"># we get query plan (including key used)</span>
mysql&gt; explain <span class="k">select</span> * from employees where emp_no &lt; <span class="m">10005</span><span class="se">\G</span>
*************************** <span class="m">1</span>. row ***************************
id: <span class="m">1</span>
select_type: SIMPLE
table: employees
partitions: NULL
type: range
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
key_len: <span class="m">4</span>
ref: NULL
rows: 4
filtered: 100.00
rows: <span class="m">4</span>
filtered: <span class="m">100</span>.00
Extra: Using where
# Compare that to the next query which does not utilize any index
mysql&gt; explain select first_name, last_name from employees where first_name = 'Sachin'\G
*************************** 1. row ***************************
id: 1
<span class="c1"># Compare that to the next query which does not utilize any index</span>
mysql&gt; explain <span class="k">select</span> first_name, last_name from employees where <span class="nv">first_name</span> <span class="o">=</span> <span class="s1">&#39;Sachin&#39;</span><span class="se">\G</span>
*************************** <span class="m">1</span>. row ***************************
id: <span class="m">1</span>
select_type: SIMPLE
table: employees
partitions: NULL
@@ -1324,64 +1324,64 @@ possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 299113
filtered: 10.00
rows: <span class="m">299113</span>
filtered: <span class="m">10</span>.00
Extra: Using where
# Let's see how much time this query takes
mysql&gt; explain analyze select first_name, last_name from employees where first_name = 'Sachin'\G
*************************** 1. row ***************************
EXPLAIN: -&gt; Filter: (employees.first_name = 'Sachin') (cost=30143.55 rows=29911) (actual time=28.284..3952.428 rows=232 loops=1)
-&gt; Table scan on employees (cost=30143.55 rows=299113) (actual time=0.095..1996.092 rows=300024 loops=1)
<span class="c1"># Let&#39;s see how much time this query takes</span>
mysql&gt; explain analyze <span class="k">select</span> first_name, last_name from employees where <span class="nv">first_name</span> <span class="o">=</span> <span class="s1">&#39;Sachin&#39;</span><span class="se">\G</span>
*************************** <span class="m">1</span>. row ***************************
EXPLAIN: -&gt; Filter: <span class="o">(</span>employees.first_name <span class="o">=</span> <span class="s1">&#39;Sachin&#39;</span><span class="o">)</span> <span class="o">(</span><span class="nv">cost</span><span class="o">=</span><span class="m">30143</span>.55 <span class="nv">rows</span><span class="o">=</span><span class="m">29911</span><span class="o">)</span> <span class="o">(</span>actual <span class="nv">time</span><span class="o">=</span><span class="m">28</span>.284..3952.428 <span class="nv">rows</span><span class="o">=</span><span class="m">232</span> <span class="nv">loops</span><span class="o">=</span><span class="m">1</span><span class="o">)</span>
-&gt; Table scan on employees <span class="o">(</span><span class="nv">cost</span><span class="o">=</span><span class="m">30143</span>.55 <span class="nv">rows</span><span class="o">=</span><span class="m">299113</span><span class="o">)</span> <span class="o">(</span>actual <span class="nv">time</span><span class="o">=</span><span class="m">0</span>.095..1996.092 <span class="nv">rows</span><span class="o">=</span><span class="m">300024</span> <span class="nv">loops</span><span class="o">=</span><span class="m">1</span><span class="o">)</span>
# Cost(estimated by query planner) is 30143.55
# actual time=28.284ms for first row, 3952.428 for all rows
# Now lets try adding an index and running the query again
mysql&gt; create index idx_firstname on employees(first_name);
Query OK, 0 rows affected (1.25 sec)
Records: 0 Duplicates: 0 Warnings: 0
<span class="c1"># Cost(estimated by query planner) is 30143.55</span>
<span class="c1"># actual time=28.284ms for first row, 3952.428 for all rows</span>
<span class="c1"># Now lets try adding an index and running the query again</span>
mysql&gt; create index idx_firstname on employees<span class="o">(</span>first_name<span class="o">)</span><span class="p">;</span>
Query OK, <span class="m">0</span> rows affected <span class="o">(</span><span class="m">1</span>.25 sec<span class="o">)</span>
Records: <span class="m">0</span> Duplicates: <span class="m">0</span> Warnings: <span class="m">0</span>
mysql&gt; explain analyze select first_name, last_name from employees where first_name = 'Sachin';
mysql&gt; explain analyze <span class="k">select</span> first_name, last_name from employees where <span class="nv">first_name</span> <span class="o">=</span> <span class="s1">&#39;Sachin&#39;</span><span class="p">;</span>
+--------------------------------------------------------------------------------------------------------------------------------------------+
| EXPLAIN |
<span class="p">|</span> EXPLAIN <span class="p">|</span>
+--------------------------------------------------------------------------------------------------------------------------------------------+
| -&gt; Index lookup on employees using idx_firstname (first_name='Sachin') (cost=81.20 rows=232) (actual time=0.551..2.934 rows=232 loops=1)
|
<span class="p">|</span> -&gt; Index lookup on employees using idx_firstname <span class="o">(</span><span class="nv">first_name</span><span class="o">=</span><span class="s1">&#39;Sachin&#39;</span><span class="o">)</span> <span class="o">(</span><span class="nv">cost</span><span class="o">=</span><span class="m">81</span>.20 <span class="nv">rows</span><span class="o">=</span><span class="m">232</span><span class="o">)</span> <span class="o">(</span>actual <span class="nv">time</span><span class="o">=</span><span class="m">0</span>.551..2.934 <span class="nv">rows</span><span class="o">=</span><span class="m">232</span> <span class="nv">loops</span><span class="o">=</span><span class="m">1</span><span class="o">)</span>
<span class="p">|</span>
+--------------------------------------------------------------------------------------------------------------------------------------------+
1 row in set (0.01 sec)
<span class="m">1</span> row <span class="k">in</span> <span class="nb">set</span> <span class="o">(</span><span class="m">0</span>.01 sec<span class="o">)</span>
# Actual time=0.551ms for first row
# 2.934ms for all rows. A huge improvement!
# Also notice that the query involves only an index lookup,
# and no table scan (reading all rows of table)
# ..which vastly reduces load on the DB.
</code></pre>
<p><em>Workshop 3: Identify slow queries on a MySQL server</em></p>
<pre><code># Run the command below in two terminal tabs to open two shells into the container.
docker exec -it $(docker ps -qf &quot;name=db&quot;) bash
<span class="c1"># Actual time=0.551ms for first row</span>
<span class="c1"># 2.934ms for all rows. A huge improvement!</span>
<span class="c1"># Also notice that the query involves only an index lookup,</span>
<span class="c1"># and no table scan (reading all rows of table)</span>
<span class="c1"># ..which vastly reduces load on the DB.</span>
</code></pre></div></p>
<p><em>Workshop 3: Identify slow queries on a MySQL server</em>
<div class="highlight"><pre><span></span><code><span class="c1"># Run the command below in two terminal tabs to open two shells into the container.</span>
docker <span class="nb">exec</span> -it <span class="k">$(</span>docker ps -qf <span class="s2">&quot;name=db&quot;</span><span class="k">)</span> bash
# Open a mysql prompt in one of them and execute this command
# We have configured to log queries that take longer than 1s,
# so this sleep(3) will be logged
<span class="c1"># Open a mysql prompt in one of them and execute this command</span>
<span class="c1"># We have configured to log queries that take longer than 1s,</span>
<span class="c1"># so this sleep(3) will be logged</span>
mysql -uroot -prealsecret mysql
mysql&gt; sleep(3);
mysql&gt; sleep<span class="o">(</span><span class="m">3</span><span class="o">)</span><span class="p">;</span>
# Now, in the other terminal, tail the slow log to find details about the query
<span class="c1"># Now, in the other terminal, tail the slow log to find details about the query</span>
root@62c92c89234d:/etc# tail -f /var/log/mysqlslow.log
/usr/sbin/mysqld, Version: 8.0.21 (MySQL Community Server - GPL). started with:
Tcp port: 3306 Unix socket: /var/run/mysqld/mysqld.sock
/usr/sbin/mysqld, Version: <span class="m">8</span>.0.21 <span class="o">(</span>MySQL Community Server - GPL<span class="o">)</span>. started with:
Tcp port: <span class="m">3306</span> Unix socket: /var/run/mysqld/mysqld.sock
Time Id Command Argument
# Time: 2020-11-26T14:53:44.822348Z
# User@Host: root[root] @ localhost [] Id: 9
# Query_time: 5.404938 Lock_time: 0.000000 Rows_sent: 1 Rows_examined: 1
use employees;
# Time: 2020-11-26T14:53:58.015736Z
# User@Host: root[root] @ localhost [] Id: 9
# Query_time: 10.000225 Lock_time: 0.000000 Rows_sent: 1 Rows_examined: 1
SET timestamp=1606402428;
select sleep(3);
</code></pre>
<span class="c1"># Time: 2020-11-26T14:53:44.822348Z</span>
<span class="c1"># User@Host: root[root] @ localhost [] Id: 9</span>
<span class="c1"># Query_time: 5.404938 Lock_time: 0.000000 Rows_sent: 1 Rows_examined: 1</span>
use employees<span class="p">;</span>
<span class="c1"># Time: 2020-11-26T14:53:58.015736Z</span>
<span class="c1"># User@Host: root[root] @ localhost [] Id: 9</span>
<span class="c1"># Query_time: 10.000225 Lock_time: 0.000000 Rows_sent: 1 Rows_examined: 1</span>
SET <span class="nv">timestamp</span><span class="o">=</span><span class="m">1606402428</span><span class="p">;</span>
<span class="k">select</span> sleep<span class="o">(</span><span class="m">3</span><span class="o">)</span><span class="p">;</span>
</code></pre></div></p>
<p>These were simulated examples with minimal complexity. In real life, the queries would be much more complex and the explain/analyze and slow query logs would have more details.</p>
@@ -1398,40 +1398,38 @@ select sleep(3);
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@@ -1465,19 +1463,13 @@ select sleep(3);
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