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Prophet: Forecasting our Metrics (or Predicting the Future)

In this blog post, we’ll look at how Prophet can forecast metrics.

Facebook recently released a forecasting tool called Prophet. Prophet can forecast a particular metric in which we have an interest. It works by fitting time-series data to get a prediction of how that metric will look in the future.

For example, it could be used to:

  • Predict how much HTTP traffic we will get, and scale accordingly when needed
  • See if a particular feature of our application will have success or if its usage will decline
  • Get an approximate date when our database server’s resources will be exhausted
  • Forecast new customer’s sign up and resize the staff accordingly
  • See what next year’s Black Friday or Cyber Monday will look like, and if we have the resources to handle them
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Asynchronous Replication from MySQL Cluster

MySQL Cluster is a highly available, distributed, shared-nothing database with very interesting performance characteristics for some workloads. Among other features, it supports automatic sharding and allows us to bypass the SQL layer if we don’t need it, via the NDB API (which in my eyes, makes it one of the few transactional nosql databases out there).

In this post, I’ll describe how we can set up replication from MySQL Cluster into a standalone MySQL server using Innodb as the storage engine.

Introduction

There are a few reasons to set up replication between MySQL Cluster and a non-NDB based MySQL server. These reasons include (but are not limited to): the need …

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Log Buffer #507: A Carnival of the Vanities for DBAs

This Log Buffer edition covers Oracle, SQL Server and MySQL blog posts with a touch of Cloud.

Oracle:

Provisioning EBS on Oracle Cloud: Latest Enhancements

ORA-54002 when trying to create Virtual Column using REGEXP_REPLACE on Oracle 12cR2

Business rules, common sense and query performance

Problem with V$RECOVERY_AREA_USAGE view and FRA space not being reclaimed

Updated …

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Percona XtraDB Cluster 5.7.17-27.20 is now available

Percona announces the release of Percona XtraDB Cluster 5.7.17-27.20 on March 16, 2017. Binaries are available from the downloads section or our software repositories.

NOTE: You can also run Docker containers from the images in the Docker Hub repository.

Percona XtraDB Cluster 5.7.17-27.20 is now the current release, based on the following:

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Column Store Database Benchmarks: MariaDB ColumnStore vs. Clickhouse vs. Apache Spark

This blog shares some column store database benchmark results, and compares the query performance of MariaDB ColumnStore v. 1.0.7 (based on InfiniDB), Clickhouse and Apache Spark.

I’ve already written about ClickHouse (Column Store database).

The purpose of the benchmark is to see how these three solutions work on a single big server, with many CPU cores and large amounts of RAM. Both systems are massively parallel (MPP) database systems, so they should use many cores for SELECT queries.

For the benchmarks, I chose …

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MySQL 5.7: Improved JOIN Order by Taking Condition Filter Effect into Account

One of the major challenges of query optimizers is to correctly estimate how many rows qualify from each table of a join. If the estimates are wrong, the optimizer may choose a non-optimal join order.

Before MySQL 5.7, the estimated number of rows from a table only took into account the conditions from the WHERE clause that were used to set up the access method (e.g., the size of an index range scan). This often led to row estimates that were far too high, resulting in very wrong cost estimates for join plans. To improve this issue, MySQL 5.7 introduced a cost model that considered the entire WHERE condition when estimating the number of qualifying rows from each table. This model estimates the filtering effect of the table’s conditions.

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Jeudis du Libre – Mons

Yesterday I was invited to speak at the “Jeudis du Libre” in Mons.

The location was very special as it was in one auditorium of Polytech, the oldest university in the city of Mons.

I presented in French two very hot topics in the MySQL ecosystem:

  • MySQL InnoDB Cluster
  • MySQL as Document Store with JSON datatype & X plugin

Those are very new technologies illustrating MySQL’s innovation. And of course there is much more to come with MySQL 8 !

Here are the slides if you are interested:

Jeudis du Libre – MySQL InnoDB Cluster from Frederic Descamps

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Monitoring Databases: A Product Comparison

In this blog post, I will discuss the solutions for monitoring databases (which includes alerting) I have worked with and recommended in the past to my clients. This survey will mostly focus on MySQL solutions. 

One of the most common issues I come across when working with clients is monitoring and alerting. Many times, companies will fall into one of these categories:

  • No monitoring or alerting. This means they have no idea what’s going on in their environment whatsoever.
  • Inadequate monitoring. Maybe people in this camp are using a platform that just tells them the database is up or connections are happening, but there is no insight into what the database is doing.
  • Too much monitoring and alerting. Companies in this camp have tons of dashboards filled with graphs, and their inbox is full of alerts that get promptly ignored. This type of monitoring is just as useful as the first option. Alert …
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New collations in MySQL 8.0.0

Since MySQL 5.5, MySQL has supported the utf8mb4 character set.  With the character-set defining the repertoire of characters that can be stored (utf8mb4 can present Unicode characters from U+0000 to U+10FFFF), a collation defines how sorting order and comparisons should behave.…

Quiz: Drop non-global users

Somebody asked on Freenode. I don’t know why they wanted it. How would you drop all MySQL users who do not have “GRANT ALL ON *.* … WITH GRANT OPTION”? That is, drop any users who have ‘N’ in any of the privilege columns in `mysql`.`user`.

My solution shown below. Did you think of a different approach?

My solution ▼

I used SQL to build SQL which built more SQL. Get the list of ‘priv’ columns from information_schema.columns. Build a query that looks for ‘N’ in any of those columns (it feels funny to search for a constant in a list of fields instead of a field in a list of constants, but it’s perfectly legal). Use the results to build the DROP USER statement.

mysql -BNe "SELECT CONCAT('SELECT CONCAT(''DROP USER '', QUOTE(user), ''@'', QUOTE(Host), '';'') FROM mysql.user WHERE ''N'' IN (', GROUP_CONCAT(column_name), ')') FROM information_schema.columns WHERE table_schema = 'mysql' AND …
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