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MUO – Feed

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A critical skill for any rifle shooter, mounting your own scope will save you time, money, and teach a core skill for long range shooting.Recoil

There are two types of IFs in MySQL: the IF statement and the IF function. Both are different from each other.  In this article, we will explain their diversities and show usage examples. Also, we will review other MySQL functions. Contents MySQL IF statements MySQL IF-THEN statement MySQL IF-THEN-ELSE statement MySQL IF-THEN-ELSEIF-ELSE statement Examples of […]

The post MySQL IF – Function and Statement (with Examples) appeared first on Devart Blog.

Planet MySQL

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I am a big fan of Percona Monitoring and Management (PMM) and am happy to report that setting up Percona Platform is as easy to set up and offers a lot of value. Percona Platform reached GA status recently and I think you will find it a handy addition to your infrastructure.

What is Percona Platform?

Percona Platform brings together enterprise-level distributions of MySQL, PostgreSQL, and MongoDB plus it includes a range of open source tools for data backup, availability, and management. The core is PMM which provides database management, monitoring, and automated insights, making it easier to manage database deployments. The number of sites with more than 100 separate databases has grown rapidly in the past few years.  Being able to have command and control of that many instances from a CLI has become impossible. Businesses need to move faster in increasingly complex environments which puts ever-increasing pressure on database administrators, developers, and everyone involved in database operations. The spiraling levels of demand make it harder to support, manage, and correct issues in database environments.

What Percona Platform provides is a unified view of the health of your entire database environment to quickly visually identify and remediate issues.  Developers can now self-service many of their database demands quickly and efficiently so they can easily provision and manage databases on a self-service basis across test and production instances. So you spend fewer resources and time on the management of database complexity.

The two keys to Percona Platform are Query Analytics (QAN), which provides granular insights into database behavior and helps uncover new database performance patterns for in-depth troubleshooting and performance optimization, and Percona Advisors, which are automated insights, created by Percona Experts to identify important issues for remediation such as security vulnerabilities, misconfigurations, performance problems, policy compliance, and database design issues. Automated insights within Percona Monitoring and Management ensure your database performs at its best. The Advisors check for replication inconsistencies, durability issues, password-less users, insecure connections, unstable OS configuration, and search for available performance improvements among other functions. 

Percona Platform is a point of control for your database infrastructure and augments PMM to be even more intelligent when connected to the Percona Platform. By connecting PMM with the Percona Platform, you get more advanced Advisors, centralized user account management, access to support tickets, private Database as a Service, Percona Expertise with the fastest SLAs, and more.

So How Do I Install Percona Platform?

The first step is to install PMM by following the Quick Start Guide. You need version 2.2.7 or later.

Second, You will need a Percona Account.

Third, you will need to connect that account to PMM.

I will assume that you will already have PMM installed.  Did I mention that PMM is free, open source software?

Now you can create a name for your organization.

Now login to your PMM dashboard and select the Settings / Percona Platform.  You will need to get your ‘Public Address’ which the browser can populate the value for you if need be.

The PMM Server ID is automatically generated by PMM.  You will need to provide a name for your server, and you will need a second browser window to login into Percona Platform to get the Percona Platform Access Token (this token has a thirty-minute lifetime, so be quick or regenerate another token).

Go back into PMM, paste the Access Token into the Percona Platform Access Token field, and click Connect.

On the Percona Platform page, you will see your PMM instances. Congratulations, you are using Percona Platform!

Advisor Checks

All checks are hosted on Percona Platform. PMM Server automatically downloads them from here when the Advisors and Telemetry options are enabled in PMM under Configuration > Settings > Advanced Settings. Both options are enabled by default.

Depending on the entitlements available for your Percona Account, the set of advisor checks that PMM can download from Percona Platform differ in terms of complexity and functionality.

If your PMM instance is not connected to Percona Platform, PMM can only download the basic set of Anonymous advisor checks. As soon as you connect your PMM instance to Percona Platform, has access to additional checks, available only for Registered PMM instances.

If you are a Percona customer with a Percona Customer Portal account, you also get access to Paid checks, which offer more advanced database health information. A list is provided below.

Check Name	Description	Tier
MongoDB Active vs Available Connections	Checks the ratio between Active and Available connections.	Registered, Paid
MongoDB Authentication	Warns if MongoDB authentication is disabled.	Anonymous, Registered, Paid
MongoDB Security AuthMech	Warns if MongoDB is not using the default SHA-256 hashing as SCRAM authentication method.	Paid
MongoDB IP Bindings	Warns if MongoDB network binding is not set as recommended.	Anonymous, Registered, Paid
MongoDB CVE Version	Shows an error if MongoDB or Percona Server for MongoDB version is not the latest one with CVE fixes.	Anonymous, Registered, Paid
MongoDB Journal Check	Warns if journal is disabled.	Registered, Paid
MongoDB Localhost Authentication Bypass is Enabled	Warns if MongoDB localhost bypass is enabled.	Anonymous, Registered, Paid
MongoDB Non-Default Log Level	Warns if MongoDB is not using the default log level.	Paid
MongoDB Profiling Level	Warns when the MongoDB profile level is set to collect data for all operations.	Registered, Paid
MongoDB Read Tickets	Warns if MongoDB is using more than 128 read tickets.	Paid
MongoDB Replica Set Topology	Warns if the Replica Set cluster has less than three members.	Registered, Paid
MongoDB Version	Warns if MongoDB or Percona Server for MongoDB version is not the latest one.	Anonymous, Registered, Paid
MongoDB Write Tickets	Warns if MongoDB network is using more than 128 write tickets.	Paid
Check if Binaries are 32-bits	Notifies if version_compatible_machine equals i686.	Anonymous, Registered, Paid
MySQL Automatic User Expired Password	Notifies if version_compatible_machine equals i686.	Registered, Paid
MySQL InnoDB flush method and File Format check	Checks the following settings: innodb_file_format, innodb_file_format_max, innodb_flush_method and innodb_data_file_path	Registered, Paid
MySQL Checks based on values of MySQL configuration variables	Checks the following settings: innodb_file_format,innodb_file_format_max,innodb_flush_method and innodb_data_file_path.	Paid
MySQL Binary Logs checks, Local infile and SQL Mode checks	Warns about non-optimal settings for Binary Log, Local Infile and SQL mode.	Registered, Paid
MySQL Configuration Check	Warns if parameters are not following Percona best practices, for infile, replication threads, and replica checksum.	Paid
MySQL Users With Granted Public Networks Access	Notifies about MySQL accounts allowed to be connected from public networks.	Registered, Paid
MySQL User Check	Runs a high-level check on user setup	Registered, Paid
MySQL Advanced User Check	Runs a detailed check on user setup	Paid
MySQL Security Check	Runs a detailed check on user setup	Paid
MySQL Test Database	This check returns a notice if there is a database with name ‘test’ or ‘test_%’.	Registered, Paid
MySQL Version	Warns if MySQL, Percona Server for MySQL, or MariaDB version is not the latest one.	Anonymous, Registered, Paid
PostgreSQL Archiver is Failing	Verifies if the archiver has failed.	Paid
PostgreSQL Cache Hit Ratio	Checks database hit ratio and complains when this is too low.	Paid
PostgreSQL Configuration Change Requires Restart/Reload	Warns when a configuration was changed and requires a server restart/reload	Registered, Paid
PostgreSQL fsync is Disabled	Shows an error if the fsync configuration is disabled, as this can result in unrecoverable data corruption.	Anonymous, Registered, Paid
PostgreSQL Autovacuum Logging Is Disabled	Shows an error if the fsync configuration is disabled, as this can result in unrecoverable data corruption.	Paid
PostgreSQL Checkpoints Logging Is Disabled	Notifies if the log_checkpoints configuration option is not enabled.	Paid
PostgreSQL Max_connections is too high	Notifies if the max_connections setting is set above 300.	Anonymous, Registered, Paid
PostgreSQL Stale Replication Slot	Warns for stale replication slots since these can lead to WAL file accumulation and DB server outage.	Paid
PostgreSQL Super Role	Notifies if there are users with superuser privileges.	Anonymous, Registered, Paid
PostgreSQL Version Check	Warns if the PostgreSQL minor or major versions are not the latest, and shows an error if the major version is 9.4 or older.	Anonymous, Registered, Paid

More Advisors will be added and Perona always welcomes contributions. Check out Percona Platform today!

 

Percona Database Performance Blog

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With all the recent talk about removing guns from the hands of law-abiding citizens, I think it’s a good time to revisit this video from back in 2019.

Not the Bee

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The Babylon Bee

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Link

(PG-13: Gore) As Star Wars fans know, stormtroopers have a long history of missing their targets. Corridor imagines how differently things might have turned out if the Empire’s plastic-armored troops just a bit more practice. Bonus VFX points for Han Solo’s mustache.

The Awesomer

Some sources of financial data can be expensive or difficult to find. For example, some is only available from exchanges or vendors who charge a hefty fee for access. However, the financial industry is also heavily regulated, and one of its main regulators provides free access to its data. The (U.S. Securities and Exchange Commission)[https://www.sec.gov] … Continue reading An introduction to accessing financial data in EDGAR, using Python

The post An introduction to accessing financial data in EDGAR, using Python appeared first on wrighters.io.

Planet Python

MySQL Partitioned Tables

Learning Outcomes

• Learn about List Partitioning.
• Learn about Range Partitioning.
• Learn about Columns Partitioning.
• Learn about Hash Partitioning.
• Learn about Key Partitioning.
• Learn about Subpartitioning.

Lesson Material

MySQL supports partitioning of tables. It supports range, list, hash, and key partitioning. Range partitioning lets you partition based on column values that fall within given ranges. List partitioning lets you partition based on columns matching one of a set of discrete values. Hash partitioning lets you partition based on the return value from a user-defined expression (the result from a stored SQL/PSM function). Key partitioning performs like hash partitioning, but it lets a user select one or more columns from the set of columns in a table; a hash manages the selection process for you. A hash is a method of organizing keys to types of data, and hashes speed access to read and change data in tables.

Each of the following subsections discusses one of the supported forms of partitioning in MySQL. Naturally, there are differences between other databases and MySQL’s implementation.

List Partitioning

A MySQL list partition works by identifying a column that contains an integer value, the franchise_number in the following example. Partitioning clauses follow the list of columns and constraints and require a partitioning key to be in the primary key or indexed.

The following list partition works with literal numeric values. MySQL uses the IN keyword for list partitions. Note that there’s no primary key designated and an index is on the auto-incrementing surrogate key column. A complete example is provided to avoid confusion on how to index the partitioning key:

CREATE TABLE franchise
( franchise_id     INT UNSIGNED AUTO_INCREMENT
, franchise_number INT UNSIGNED
, franchise_name   VARCHAR(20)
, city             VARCHAR(20)
, state            VARCHAR(20)
, index idx (franchise_id))
PARTITION BY LIST(franchise_number)
( PARTITION offshore VALUES IN (49,50)
, PARTITION west VALUES IN (34,45,48)
, PARTITION desert VALUES IN (46,47)
, PARTITION rockies VALUES IN (38,41,42,44));

The inclusion of a PRIMARY KEY constraint on the franchise_id column would trigger an ERROR 1503 when the partitioning key isn’t the primary key. The reason for the error message is that a primary key implicitly creates a unique index, and that index would conflict with the partitioning by list instruction. The use of a non-unique idx index on the franchise_id column is required when you want to partition on a non-primary key column.

Range Partitioning

Range partitioning works only with an integer value or an expression that resolves to an integer against the primary key column. The limitation of the integer drives the necessity of choosing an integer column for range partitioning. You can’t define a range-partitioned table with a PRIMARY KEY constraint unless the primary key becomes your partitioning key, like
the one below.

CREATE TABLE ordering
( ordering_id     INT UNSIGNED AUTO_INCREMENT
, item_id         INT UNSIGNED
, rental_amount   DECIMAL(15,2)
, rental_date     DATE
, index idx (ordering_id))
PARTITION BY RANGE(item_id)
( PARTITION jan2011 VALUES LESS THAN (10000) , PARTITION feb2011 VALUES LESS THAN (20000) , PARTITION mar2011 VALUES LESS THAN (30000));

Range partitioning is best suited to large tables that you want to break into smaller pieces based on the integer column. You can also use stored functions that return integers as the partitioning key instead of the numeric literals shown. Few other options are available in MySQL.

Columns Partitioning

Columns partitioning is a new variant of range and list partitioning. It is included in MySQL 5.5 and forward. Both range and list partitioning work on an integer-based column (using TINYINT, SMALLINT, MEDIUMINT, INT [alias INTEGER], and BIGINT). Columns partitioning extends those models by expanding the possible data types for the partitioning column to include CHAR, VARCHAR, BINARY, and VARBINARY string data types, and DATE, DATETIME, or TIMESTAMP data types. You still can’t use other number data types such as DECIMAL and FLOAT. The TIMESTAMP data type is also available only in range partitions with the caveat that you use a UNIX_TIMESTAMP function, according to MySQL Bug 42849.

Hash Partitioning

Hash partitions ensure an even distribution of rows across a predetermined number of partitions. It is probably the easiest way to partition a table quickly to test the result of partitioning on a large table. You should base hash partitions on a surrogate or natural primary key.

The following provides a modified example of the ordering table:

CREATE TABLE ordering
( ordering_id       INT UNSIGNED PRIMARY KEY AUTO_INCREMENT
, item_id           INT UNSIGNED
, rental_amount     DECIMAL(15,2)
, rental_date       DATE)
PARTITION BY HASH(ordering_id) PARTITIONS 8;

This is the partitioning type that benefits from a PRIMARY KEY constraint because it automatically creates a unique index that can be used by the hash. A non-unique index such as the list partitioning example doesn’t work for a hash partition.

Key Partitioning

Key partitioning is valuable because you can partition on columns that aren’t integers. It performs along the line of hash partitioning, except the MySQL Server uses its own hashing expression.

CREATE TABLE orders_list
( order_list_id     INT UNSIGNED AUTO_INCREMENT
, customer_surname  VARCHAR(30)
, store_id          INT UNSIGNED
, salesperson_id    INT UNSIGNED
, order_date        DATE
, index idx (order_list_id))
PARTITION BY KEY (order_date) PARTITIONS 8;

This is the only alternative when you want to partition by date ranges. Like the hash partition, it’s easy to deploy. The only consideration is the number of slices that you want to make of the data in the table.

Subpartitioning

The concept of subpartitioning is also known as composite partitioning. You can subpartition range or list partitions with a hash, linear hash, or linear key.

A slight change to the previously created ordering table is required to demonstrate composite partitioning: we’ll add a store_id column to the table definition. The following is an example of a range partition subpartitioned by a hash:

CREATE TABLE ordering
INT UNSIGNED
INT UNSIGNED
DATE
 ( ordering_id     INT UNSIGNED AUTO_INCREMENT
, item_id          INT UNSIGNED
, store_id         INT UNSIGNED
, rental_amount    DECIMAL(15,2)
, rental_date      DATE
, index idx (ordering_id))
PARTITION BY RANGE(item_id)
  SUBPARTITION BY HASH(store_id) SUBPARTITIONS 4
( PARTITION jan2011 VALUES LESS THAN (10000)
, PARTITION feb2011 VALUES LESS THAN (20000)
, PARTITION mar2011 VALUES LESS THAN (30000));

Composite partitioning is non-trivial and might require some experimentation to achieve optimal results. Plan on making a few tests of different scenarios before you deploy a solution.

Planet MySQL