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Displaying posts with tag: Architecture (reset)
Infiniflash Benchmark

Sandisk (FusionIO) and Nexenta are working together to build this SDS solution.

Infiniflash is a very large SDS production, which manages for very large DW system who requires large storage space and also high IOPS.

We test infiniflash system ,read this Infiniflash_benchmark

MySQL distributed message system

Based on messages, we create mysql replication platforms , using async message to build strong distributed subscription system.

read this PDF : http://www.vmcd.org/docs/MySQL_async_message.pdf

Using Triggers On Schemaless, Uber Engineering’s Datastore Using MySQL

The details and examples of Schemaless triggers, a key feature of the datastore that’s kept Uber Engineering scaling since October 2014. This is the third installment of a three-part series on Schemaless; the first part is a design overview

The post Using Triggers On Schemaless, Uber Engineering’s Datastore Using MySQL appeared first on Uber Engineering Blog.

The Architecture of Schemaless, Uber Engineering’s Trip Datastore Using MySQL

How Uber’s infrastructure works with Schemaless, the datastore using MySQL that’s kept Uber Engineering scaling since October 2014. This is part two of a three-part series on Schemaless; part one is on designing Schemaless.

In Project Mezzanine:

The post The Architecture of Schemaless, Uber Engineering’s Trip Datastore Using MySQL appeared first on Uber Engineering Blog.

Designing Schemaless, Uber Engineering’s Scalable Datastore Using MySQL

The making of Schemaless, Uber Engineering’s custom designed datastore using MySQL, which has allowed us to scale from 2014 to beyond. This is part one of a three-part series on Schemaless.

In Project Mezzanine we described how we migrated Uber’s …

The post Designing Schemaless, Uber Engineering’s Scalable Datastore Using MySQL appeared first on Uber Engineering Blog.

Motivation to Migrate RDBMS

http://www.itnews.com/article/3004953/use-oracles-database-watch-out-for-this-dec-1-deadline.html

Companies that use a standard edition of Oracle’s database software should be aware that a rapidly approaching deadline could mean increased licensing costs.

Speaking from experience (at both MySQL AB and Open Query), typically, licensing/pricing changes such as these act as a motivator for migrations.

Migrations are a nuisance (doesn’t matter from/to what platform) and are best avoided as they’re intrinsically painful, costly and time-consuming. Smart companies know this.

When asked in generic terms, we generally recommend against migrations (even to MySQL/MariaDB) for the above-mentioned practical and business reasons. There are also technical reasons. I’ll list a …

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TokuDB benchmark on PCIe

MariaDB TokuDB benchmark on FusionIO ,Compare TokuDB and InnoDB engines.

read: TokuDB_benchmark

How to configure AWR system

In this article, we introduce myawr and mongoawr system .

Read this PDF, you will learn how to configure them.

How to configure AWR system.

How to configure Tcpdump system

MySQL Tcpdump system : use percona-toolkit to analyze network packages

We can identify problem SQLs with high execution frequency.

With DBMON system and AWR system we can find problem SQLs in a special time (high frequency, occurs over a period of time)

View this PDF:

http://www.vmcd.org/docs/MySQL_TCPDUMP.pdf

Architecture of data warehouse which is based on MQ

Recently, we create a mysql data warehouse which is based on message queue.

Most companies must prepare for particular queries in their systems if they consider to split their databases or tables into many pieces.

some problems should be solved in this situation:

1. how to get correct results in-time
2. how to build strong data warehouse for future analyst

These policies were used by YHD

They have already deployed a middle-ware layer to support these requests (between web apps and databases). Every aggregation SQL was splited into many small SQLs and runs in every data nodes.The Final result is the aggregation of these all small SQLs. In this procedure, everything was computed in memory to get high performance.

In data warehouse layer, they use self-defined ETL tools to extract data from different databases to oracle-Exadata platform. Log-based data was put into hadoop and hbase.

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