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2012-06-22ntdb: take advantage of direct access across expand.Rusty Russell1-33/+15
This means we no longer have to unmap if we want to compare a record. Signed-off-by: Rusty Russell <rusty@rustcorp.com.au>
2012-06-19ntdb: optimize ntdb_fetch.Rusty Russell1-14/+23
We access the key on lookup, then access the data in the caller. It makes more sense to access both at once. We also put in a likely() for the case where the hash is not chained. Before: Adding 1000 records: 3644-3724(3675) ns (129656 bytes) Finding 1000 records: 1596-1696(1622) ns (129656 bytes) Missing 1000 records: 1409-1525(1452) ns (129656 bytes) Traversing 1000 records: 1636-1747(1668) ns (129656 bytes) Deleting 1000 records: 3138-3223(3175) ns (129656 bytes) Re-adding 1000 records: 3278-3414(3329) ns (129656 bytes) Appending 1000 records: 5396-5529(5426) ns (253312 bytes) Churning 1000 records: 9451-10095(9584) ns (253312 bytes) smbtorture results (--entries=1000) ntdb speed 183881-191112(188223) ops/sec After: Adding 1000 records: 3590-3701(3640) ns (129656 bytes) Finding 1000 records: 1539-1605(1566) ns (129656 bytes) Missing 1000 records: 1398-1440(1413) ns (129656 bytes) Traversing 1000 records: 1629-2015(1710) ns (129656 bytes) Deleting 1000 records: 3118-3236(3163) ns (129656 bytes) Re-adding 1000 records: 3235-3355(3275) ns (129656 bytes) Appending 1000 records: 5335-5444(5385) ns (253312 bytes) Churning 1000 records: 9350-9955(9494) ns (253312 bytes) smbtorture results (--entries=1000) ntdb speed 180559-199981(195106) ops/sec
2012-06-19ntdb: remove hash table trees.Rusty Russell1-655/+395
TDB2 started with a top-level hash of 1024 entries, divided into 128 groups of 8 buckets. When a bucket filled, the 8 bucket group expanded into pointers into 8 new 64-entry hash tables. When these filled, they expanded in turn, etc. It's a nice idea to automatically expand the hash tables, but it doesn't pay off. Remove it for NTDB. 1) It only beats TDB performance when the database is huge and the TDB hashsize is small. We are about 20% slower on medium-size databases (1000 to 10000 records), worse on really small ones. 2) Since we're 64 bits, our hash tables are already twice as expensive as TDB. 3) Since our hash function is good, it means that all groups tend to fill at the same time, meaning the hash enlarges by a factor of 128 all at once, leading to a very large database at that point. 4) Our efficiency would improve if we enlarged the top level, but that makes our minimum db size even worse: it's already over 8k, and jumps to 1M after about 1000 entries! 5) Making the sub group size larger gives a shallower tree, which performs better, but makes the "hash explosion" problem worse. 6) The code is complicated, having to handle delete and reshuffling groups of hash buckets, and expansion of buckets. 7) We have to handle the case where all the records somehow end up with the same hash value, which requires special code to chain records for that case. On the other hand, it would be nice if we didn't degrade as badly as TDB does when the hash chains get long. This patch removes the hash-growing code, but instead of chaining like TDB does when a bucket fills, we point the bucket to an array of record pointers. Since each on-disk NTDB pointer contains some hash bits from the record (we steal the upper 8 bits of the offset), 99.5% of the time we don't need to load the record to determine if it matches. This makes an array of offsets much more cache-friendly than a linked list. Here are the times (in ns) for tdb_store of N records, tdb_store of N records the second time, and a fetch of all N records. I've also included the final database size and the smbtorture local.[n]tdb_speed results. Benchmark details: 1) Compiled with -O2. 2) assert() was disabled in TDB2 and NTDB. 3) The "optimize fetch" patch was applied to NTDB. 10 runs, using tmpfs (otherwise massive swapping as db hits ~30M, despite plenty of RAM). Insert Re-ins Fetch Size dbspeed (nsec) (nsec) (nsec) (Kb) (ops/sec) TDB (10000 hashsize): 100 records: 3882 3320 1609 53 203204 1000 records: 3651 3281 1571 115 218021 10000 records: 3404 3326 1595 880 202874 100000 records: 4317 3825 2097 8262 126811 1000000 records: 11568 11578 9320 77005 25046 TDB2 (1024 hashsize, expandable): 100 records: 3867 3329 1699 17 187100 1000 records: 4040 3249 1639 154 186255 10000 records: 4143 3300 1695 1226 185110 100000 records: 4481 3425 1800 17848 163483 1000000 records: 4055 3534 1878 106386 160774 NTDB (8192 hashsize) 100 records: 4259 3376 1692 82 190852 1000 records: 3640 3275 1566 130 195106 10000 records: 4337 3438 1614 773 188362 100000 records: 4750 5165 1746 9001 169197 1000000 records: 4897 5180 2341 83838 121901 Analysis: 1) TDB wins on small databases, beating TDB2 by ~15%, NTDB by ~10%. 2) TDB starts to lose when hash chains get 10 long (fetch 10% slower than TDB2/NTDB). 3) TDB does horribly when hash chains get 100 long (fetch 4x slower than NTDB, 5x slower than TDB2, insert about 2-3x slower). 4) TDB2 databases are 40% larger than TDB1. NTDB is about 15% larger than TDB1
2012-06-19ntdb: remove ntdb_error()Rusty Russell1-4/+3
It was a hack to make compatibility easier. Since we're not doing that, it can go away: all callers must use the return value now. Signed-off-by: Rusty Russell <rusty@rustcorp.com.au>
2012-06-19TDB2: Goodbye TDB2, Hello NTDB.Rusty Russell1-0/+894
This renames everything from tdb2 to ntdb: importantly, we no longer use the tdb_ namespace, so you can link against both ntdb and tdb if you want to. This also enables building of standalone ntdb by the autobuild script. Signed-off-by: Rusty Russell <rusty@rustcorp.com.au>