Maching Learning for Indexing
Contents
The following are the learnings from the podcast:
- Indexing was the realm of DBA experts
- Machine learning to learn to indexing
- Simple ML algos to complex algos are being used to learn the index maps
- Btrees, Hashmaps, Bloomfilters - typical algos to build indices
- DBA will need to become machine learning experts
- Many areas such as query optimisation, multivariate indexing learning models, indexing for inserts are all the exciting new development s waiting to happen
- Data distribution changes- custom indexing atrategies do not work anymore
- Use GPU to train models
- Indexes- used for preprocessing
- Btrees - Range of records
- Hashmaps- Specific queries
- Bloom filters- efficient storage
- Change in complexity class for a specific kind of indexing
- Log(n) space to constant time
- Btrees speed up 2x - Indexes significant reduction in space
- Supervised learning
- Latency in nanoseconds
- Redix Sort
- Training time is dependent on the algo