The common problem
Big data is something that is always curtail to your business as information is power. Although it is quite common to witness the degrading of your Big Data performance there are several means of fighting it. Yet you have to know what to fight and when to begin the battle. What are the S.O.S. signals your data is giving you before it actually begging to work slower than a sea turtle stranded in the desert on a sunny afternoon? When to rampage on the responsible department for them to take appropriate measures in time to prevent rather than to defeat?
When talking Big Data monitoring is of your primary tools. If any routine query is taking 1 or more second to execute that is a distress call. A call for help you are to notice. 1 second is the signal Big Trouble are about to emerge somewhere throughout your Big Data. What are the most common issues you will be facing after such S.O.S. signals?
- Concurrency Connection
- Slow Writes
- Table Scans
Who are these foes of data and how will your specialists be able of dealing with those? Let’s have a closer look.
We are beginning with something extremely hard to predict. Let’s imagine a single table or even a data store. It will grow along with your business. And you will be using some database indexes. That is actually what causes the traditional RDBMS engines to be a bit slower than expected. Especially if there are several indexes that are being implemented on some particular large table. What you are probably using as your index type is the B-Tree. And it is requiring some extra resources when growing in depth. And Voilà! You are experiencing a dramatic slowdown. Solution here is quite simple. Limit the index usage to only the dramatically important ones and watch out for of extremely large tables or data sizes.
This one’s really close to Table Scans. This is something that they may lead to. A good database will be serving multiple purposes of many users. That’s why it is there in the first place. That is where many forms of concurrency connections may take place. Why’s it happening? Too many users are hungry for one particular resource as if it is the ultimate kitten picture of all the internet. That’s when the database will start protecting itself by locking up. This may be easily avoided if the size of transactions is limited. You will also make sure all the write statements and the query are efficient. Never forget the 1 second maximum rule and consider this issue is managed.
This is the ugliest issue as for now. When it emerges? When your query is requesting a row or even a range of rows (which happens more often) straight from the DBMS engine. What may go wrong? There might not be the appropriate index that is supporting the query or the DBMS simply does not select it for some unknown reasons. That is when your engine is left with one option only, a sequential scan of all the data available. And you have rapid performance degradation done before your very eyes. Monitor for the 1 second rule, and you might end up with all the best even with this scenario.