3 ms·
So some questions:: 1. Isn't (3)vectorization and (4)SIMD the same thing ? 2. I don't see the data-size before-after compression ? 3. How much RAM has each
by ddorian43 9y ago
So some questions::
1. Isn't (3)vectorization and (4)SIMD the same thing ?
2. I don't see the data-size before-after compression ?
3. How much RAM has each server ?
4. How do all cores work for all queries ? Is the data sharded by core on each machine or each core can work on whatever data ?
5. What's a comparison open-source tool to this ? Only I can think about is snappydata.
- mehrdadn 9y ago(1) I don't know if this is what they're thinking, but not all single instructions that operate on "multiple data" are vector operations... e.g. I wouldn't call summing all items in an __m128 to be a vectorized operation. Similarly I suppose not all vectorized operations are SIMD, since they might just use normal (SISD) instructions on entire arrays. But again, I'm not sure this is really what they mean; it wouldn't seem to be a very useful distinction to make.
- ryanworl 9y agoFor 5, check out Clickhouse. It isn’t identical, but scanning a trillion rows a second is just a matter of sharding the data into enough nodes. https://clickhouse.yandex https://clickhouse.yandex
- plamb 9y agoSnappyData employee here. In general this is called the "HTAP" industry (Gartner's phrase: Hybrid Transactional/Analytical Processing). SnappyData: https://www.snappydata.io https://www.snappydata.io, MemSQL: https://www.memsql.com/ https://www.memsql.com/, Splice Machine: https://www.splicemachine.com/ https://www.splicemachine.com/, SAP Hana: https://www.sap.com/products/hana.html https://www.sap.com/products/hana.html, GridGain: https://www.gridgain.com/ https://www.gridgain.com/ are some of the technologies within it