I'm studying SAP HANA main memory database.
There is index called CPBTree in it. In it's document, it is described as follows:
CPB+-tree stands for Compressed Prefix B+-Tree; this index tree type is based on pkB-tree. CPB+-tree is a very small index because it uses 'partial key' that is only part of full key in index nodes.
This is a bit vague. There is no other explanation about CPBTree structure on the Internet.
Is there anyone who can explain more or introduce a good document?
Where to begin here?
B-trees are very intensely studied and developed data structures, so pointing to a single document that explains all aspects relevant to this question and SAP HANA is a bit difficult.
Maybe it helps to unpack the term first:
Compressed Prefix
This basically means, the B-tree index and leaf nodes do not contain the full strings for keys. Instead, the parts of the key-strings that are common among the keys (the prefixes) are stored separately. The leaf and index nodes then only contain
This technique is rather common in many DBMS, usually attached to a feature called "index compression" or something similar.
So, now we know that HANA uses compressed B-tree indexes (for row-store tables and for data that can be expressed as strings).
Why is this important for an in-memory database like HANA? In short: memory transfer effort between RAM and CPU. The smaller the index structure, the more of it can fit into the CPU caches. To traverse (go through) the index, fewer back-and-forth movements of data have to be performed.
It's a huge performance advantage.
This is complemented with specific "cache-conscious" index protocols (how the index structure is used by the HANA kernel) that try to minimize the RAM-CPU data transfers.
All this is an overly simplified explanation and I hope that it helps to make more sense nevertheless.
If you want to "dive deeper" and start reading academic papers around that topic then Cache-Conscious Concurrency Control of Main-Memory Indexes on Shared-Memory Multiprocessor Systems by Prof. Sang K. Cha. et al.
This is the same Sang K. Cha that created P*Time, an in-memory (row-store) DBMS in the early 2000s.
This P*Time has been, rather well-known, acquired by SAP (like so many other DBMS software products companies... Sybase... MaxDB... OrientDB...) and the technology has been used as a research base for what would become SAP HANA.
Nowadays, there is only a small part of P*Time still in SAP HANA and it is mostly reduced to the concepts and algorithms and not so much expressed in actual P*Time code.
All in all, for the user of HANA (developer, admin, data consumer) the specifics of this index implementation hardly matter as none of them can interact with the index structure directly.
What matters is that this index takes modern server systems (many cores, large CPU caches, lots of RAM) and extracts great performance from them, while still allowing for "high-speed" transactions.
I added an extended write-up of this answer to my blog: https://lbreddemann.org/what-is-cpb-tree-in-sap-hana/.
