Unbearably slow query and batch job

coding in SQL,
whatever single-machine/cluster,
whatever commercial/open-source,
whatever big name/new star

Why the running speed is so low now?

When the hardware remains unchanged, you have to design the algorithms featuring less computation amount,

and then code in an effective programming language.

Unfortunately, you cannot implement such low-complexity algorithms in SQL due to its theoretical limitation.

Then, how can I make the running speed fast?

Well, discard SQL.

Also, you should not use Java as well. Although you can implement the said algorithms in Java, it will make you exhausted.

Using SPL instead, it will allow you to implement high-performance computing with simple code.

What is SPL? Why does it work?

SPL is an open-source programming language, specializing in dealing with structured data computation. We’ve integrated dozens of high-performance algorithms and storage schemes in SPL, which make it a reality to speed up by N times!

Want to learn it? Visit: Performance Optimization, SPL Tutorial

Is it really that amazing?

Looks good, does it really work?

Can I have a try?

Sure, just a few steps:

i, provide related information;
ii, discuss in detail and do a few tests;
iii, design optimization plan.

Providing related information

Please provide us with your performance problem information, we will help you speed up by N times!
  • Business scenario and problem description, including:
    • Simply business scenario
    • Condition for initiating a query or batch job request
    • Execution frequency
    • Main problem, etc.
  • Select key characteristic targets, and accurately describe the value of business scenario, including.
    • Data volume (<100 million, 100 million - 1 billion, 1 billion - 10 billion, > 10 billion)
    • Concurrency number
    • Current key response time (_____ sec/min/hr), desired response time (_____ sec/min/hr)
  • More detailed and specific business details, including:
    • Example of SQL or stored procedure script
    • Running time or execution plan
    • Database structure like the designed table structure and data volume
    • Hardware and software environments, such as CPU (model, frequency, number of cores), memory (capacity), disk (type, capacity), operating system and version, data warehouse type and version
    • What is the crux of the problem after preliminary analysis, and what optimization attempts have been made, etc.
Once these materials are made ready, please don’t hesitate to contact us via spl@scudata.com.
Let's work together to solve the troublesome performance problem!