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We already discussed about Queue management solutions in the past, and I am always happy to write about it. Queue managers are not easy to implement, and there is a reson if IBM MQ Series is still a successful product. Some month ago, a big bank customer asked me to provide a small queue implementation to increase asynchronous internal processing of our payment solution.
The project had very strong contraints: I could not use existing queue system because they were not yet available, and I need to be able to provide microservice parallelism in a cloud-environent.
I have very little time to provide a solid solution, and re-inventing the wheel was not an option. Performance was important, but we plan to have a managable numbers of transactions per seconds, far behind modern cloud database capacity.
Challenge accepted.
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Test driven development is a beast to tame. I like TDD but in the past it was quite difficult to achive, at least in a pure-consultant approach with a "turn key" framework behind.
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Some co-workers started using Apache Kafka con a bunch of our Customers.
Apache Kafka is a community distributed event streaming platform capable of handling trillions of events a day. Initially conceived as a messaging queue, Kafka is based on an abstraction of a distributed commit log[*].
To get this goal, Apache Kafka needs a complex servers setup, even more complex if you want the certification for the producing company (Confluent). Now, if you are planning to use Kafka like a simple JavaMessaeSystem (JMS) implementation, think twice before going on this route.PostgreSQL 12 offers a fair (and open source) partition implementation, whereas if money are not a problem, Oracle 12c can happy scale on billions of record before running into troubles (and ExaData can scale even more).
PostgreSQL and Oracle offer optimizations for partitioned data, called “Partition Pruning” in PostreSQL teminology:
With partition pruning enabled, the planner will examine the definition of each partition and prove that the partition need not be scanned because it could not contain any rows meeting the query's WHERE clause. When the planner can prove this, it excludes (prunes) the partition from the query plan.
This feature is quite brand new (popped in PostreSQL 11) but it is essential to a successful partition strategy. Before these feature, partitioning was a black magic art. Now it is simpler to manage.
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In the 1980 comments were used to reduce the “gap” between unstructured code and “rationale” behind the code.
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I am studying Apache Kafka (a "distributed streaming platform") and I stumbled upon this conclusion: the "disk read fear" a lot of projects have in the past, is a fake.
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Vjdbc is a remote access for JDBC-Datasources developed more then ten years ago (last news are from 2007, with last comit from 2013.
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Today I took a light rail with my son, to bring him to school. That tram is 90 years old. It has been maintained for 90 years. Milan city sold some of them to San Francisco too.
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Sometimes in University I found bold young guy saying something like:
I will reimplement this in machine language because is faster
I will reimplement this xyz C function by my own
My program crash, I think there is a bug in HP UNIX socket implementation
I will ge rid of this Java Garbage Collector because it is too slow. I will reimplement all the code in my C++ routine.
Belive me: your code is doomed. A full list of guys have already done your same code, found a million bugs and corrected it in the tool you want to replace because they are shitty slow, to your eyes.
I feel your pain because I made your same mistake. Keep reading.
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