Webinar - MariaDB Temporal Tables: a demonstration

MariaDB Temporal Tables:
A Demonstration

● Why track data changes?
● System-versioned tables
● Application-period tables
● Bitemporal tables
● A word on MindsDB
Agenda

● Auditing
● Travel back in time
● Compare today situation with 6 months ago
● Statistics on data changes
● Find correlations
● History of an entity
● Debug
Tracking Data Changes: WHY?

● There are many ways to track data changes.
● Most commonly, they involve having a consumer that reads the
binary log and send changes to other technologies, like Kafka.
● Great for analytics, message queues, auditing.
● But the changes are:
○ Replicated asynchronously
○ Not available to the application
Tracking Data Changes

In-Database data changes tracking methods:
● Logging row versions into a table
● Logging each value change into a table
● Temporal tables

Advantages of Temporal Tables:
● The versioning logic is transparent
● Rotation can be automated
● Faster and more scalable

Existing implementations (I know about):
● Oracle 11g (2007)
● IBM Db2 (2012)
● SQL Server (2016)
● Snowflake
Temporal Tables Overview

Existing implementations (I know about):
● PostgreSQL has a temporal tables extension
● CockroachDB
● CruxDB
● HBase (kind of)

● MariaDB 10.3: system-versioned tables
● MariaDB 10.4: application period tables
A table can implement both. It's called a bitemporal table.

● Rows are versioned
● Every row has 2 timestamps, the start & end of that version
validity
● INSERT, UPDATE, DELETE modify those timestamps in a
transparent way
● Plain SQL SELECTs only return current data
● Using temporal syntax, we can query past data
System-Versioned

● Works best to describe events with a start and an end
● Especially when some events cannot overlap
● Timestamps are written explicitly by the application
● But UPDATE and DELETE can automagically shrink or split
periods
● Apart from this, they are regular tables that you use with normal
SQL syntax
Application-Period Tables

● Not understanding this damages projects.
● If you work for a vendor, whether you want to say it or not, feel
free to correct any mistake I might make

● Create a sysver table:
CREATE TABLE tbl_name (
…
valid_since TIMESTAMP(6) GENERATED ALWAYS AS ROW START
INVISIBLE,
valid_until TIMESTAMP(6) GENERATED ALWAYS AS ROW END
INVISIBLE,
PERIOD FOR SYSTEM_TIME(valid_since, valid_until)
)
WITH SYSTEM VERSIONING
;
System-Versioned Tables

Best practices:
● You could omit the column names, but then you won't be able to
use them in queries
● You can use different names, but I recommend you always use
the same names
● You could use visible columns, but most of the times you don't
want to see them

● An existing table can be made sysver:
ALTER TABLE tbl_name
ADD COLUMN valid_since TIMESTAMP(6) GENERATED
ALWAYS AS ROW START INVISIBLE,
ADD COLUMN valid_until TIMESTAMP(6) GENERATED
ALWAYS AS ROW END INVISIBLE,
ADD PERIOD FOR SYSTEM_TIME(valid_since,
valid_until),
ADD SYSTEM VERSIONING
;

Best practices:
● Making one, multiple, or even all tables sysver is not a risky
operation - but you never know
● You can do this on a new replica that is used by analysts or
programs that read historical data
● For such replicas it's usually ok not to use an LTS version
● Once you're confident enough, you can make the change on the
master

● In both cases (new or existing table), it's practical to create one
or more separate partitions for historical data:
ALTER TABLE tbl_name
PARTITION BY SYSTEM_TIME (
PARTITION p_history1 HISTORY,
… ,
PARTITION p_current CURRENT
)
;

How to delete history:
● Remove history before a point in time:
DELETE HISTORY FROM tbl_name
BEFORE SYSTEM_TIME '2020-01-01 00:00:00';
● Remove whole history:
DELETE HISTORY FROM tbl_name;
● Remove history and make the table non-sysver:
ALTER TABLE t DROP SYSTEM VERSIONING;
● Remove history and current data:
TRUNCATE TABLE tbl_name;

● GDPR and possibly some other regulations guarantee the
Right To Be Forgotten (RTBF)
● This means that we can't keep the whole history of columns that
contain Personal Identifiable Information (PII)
● To exclude these columns from a table history:
CREATE TABLE user (
…
email VARCHAR(100) NOT NULL WITHOUT SYSTEM VERSIONING,
…
)
WITH SYSTEM VERSIONING
;
Right To Be Forgotten

● Creating an Application-Period table:
CREATE OR REPLACE TABLE reservation (
uuid UUID DEFAULT UUID(),
bungalow_name VARCHAR(100) NOT NULL,
client_name VARCHAR(100) NOT NULL,
start_date DATE,
end_date DATE,
PRIMARY KEY (uuid, start_date),
PERIOD FOR reservation (start_date, end_date)
);

● If you don't use periods explicitly, it will be a regular table
● But you can manipulate periods with this syntax:
○ DELETE FROM <table_name>
FOR PORTION OF <period_name>
FROM <date1> TO <date2>
○ UPDATE <table_name>
FOR PORTION OF <period_name>
FROM <date1> TO <date2>

● Combine the syntaxes of sysver and application-period tables to
obtain a bitemporal table
● This table will store two separate pairs of timestamps:
○ When the row was physically inserted/deleted/updated
○ The boundaries of the represented period

Example:
● 2018/01/10 - Customer registers, she lives in Glasgow
● 2022/05/01 - Customer relocates to Inverness
● 2022/06/01 - Customer orders a product
● 2022/06/02 - Customer changes her address in her profile, and
correctly dates the change to 2022/05/01
Customer never received the parcel. Our temporal table allows us
to track this chronology and point out that
the customer communicated her address change too late.

● If you built Temporal Tables, you have something similar to
(but slightly more complex than) a time series
● Do you know that you can query future data?

● MindsDB is an AI-based virtual database
● It connects to a huge range of external data sources,
including MariaDB
● It accepts SQL queries
● The results are calculated using Machine Learning algorithms

So, for example, if you have data about your sales in the last 2
years, you can obtain a forecast about the next 6 months
Vettabase is MindsDB partner.
We maintain their MySQL integration.

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