On Tue, 2019-11-26 at 17:47 -0800, Daniel Phillips wrote: > Hi folks, > > Here is my somewhat tardy followup to my Three Things post from > earlier > this fall. I give you Thing 1, Shardmap. What I hope to accomplish > today > is to initiate a conversation with Ext4 developers, and other > interested > observers, which will eventually result in merging the new Shardmap > directory index code into Ext4, thereby solving a number of > longstanding > issues with the venerable and somewhat problematic HTree. > > HTree is the most used directory index in the known universe. HTree > does > some things fantastically well, particularly in the most common range > of > directory sizes, but also exhibits some well known flaws and at least > one > previously unknown flaw, explained below. Shardmap is a new index > design, > just seven years old, an O(1) extensible hash table, meant to address > all > of HTree's flaws while improving performance and scaling into the > previously inaccessible billion file per directory range. Subject to > verifying these claims, it would seem to be logical to move on to the > logistics of porting Shardmap to Ext4 as an optional index algorithm, > eventually deprecating HTree. > As far as I know, usually, a folder contains dozens or hundreds files/folders in average. There are many research works that had showed this fact. Do you mean some special use-case when folder could contain the billion files? Could you share some research work that describes some practical use-case with billion files per folder? If you are talking about improving the performance then do you mean some special open-source implementation? > Shardmap equals or outperforms HTree at all scales, with the single > exception of one theoretical case with a likewise theoretical > solution. > Shardmap is O(1) in all operations - insert, delete, lookup and > readdir, > while HTree is O(log N) in the first three and suffers from a > relatively > large constant readdir overhead. This is not the only reason Shardmap > is > faster than HTree, far from it. > > I will break performance discussion down into four ranges: > 1) unindexed single block, to about 300 entries > 2) indexed up to 30 thousand entries > 3) indexed up to 3 million entries > 4) indexed up to 1 billion entries. > > In theory, Shardmap and HTree are exactly tied in the common single > block case, because creating the index is delayed in both cases until > there are at least two blocks to index. However, Shardmap broke away > from the traditional Ext2 entry block format in order to improve > block > level operation efficiency and to prevent record fragmentation under > heavy aging, and is therefore significantly faster than HTree even in > the single block case. > > Shardmap does not function at all in the fourth range, up to 1 > billion > entries, because its Btree has at most 2 levels. This simple flaw > could be > corrected without much difficulty but Shardmap would remain superior > for > a number of reasons. > > The most interesting case is the 300 to 30 thousand entry range, > where > Htree and Shardmap should theoretically be nearly equal, each > requiring > two accesses per lookup. However, HTree does two radix tree lookups > while > Shardmap does one, and the other lookup is in a cached memory object. > Coupled with the faster record level operations, Shardmap is > significantly > faster in this range. In the 30 thousand to 3 million range, > Shardmap's > performance advantage further widens in accordance with O(1) / O(log > N). > > For inserts, Shardmap's streaming update strategy is far superior to > HTree's random index block write approach. HTree will tend to dirty > every > index block under heavy insert load, so that every index block must > be > written to media per commit, causing serious write multiplication > issues. In fact, all Btree schemes suffer from this issue, which on > the > face of it appears to be enough reason to eliminate the Btree as a > realistic design alternative. Shardmap dramatically reduces such per > commit write multiplication by appending new index entries linearly > to > the tail blocks of a small number of index shards. For delete, > Shardmap avoids write multiplication by appending tombstone entries > to > index shards, thereby addressing a well known HTree delete > performance > issue. Do you mean Copy-On-Write policy here or some special technique? How could be good Shardmap for the SSD use-case? Do you mean that we could reduce write amplification issue for NAND flash case? > > HTree has always suffered from a serious mismatch between name > storage > order and inode storage order, greatly exacerbated by the large > number > of directory entries and inodes stored per block (false sharing). In > particular, a typical HTree hash order directory traversal accesses > the > inode table randomly, multiplying both the cache footprint and write > traffic. Historically, this was the cause of many performance > complaints > about HTree, though to be sure, such complaints have fallen off with > the advent of solid state storage. Even so, this issue will continue > rear > its ugly head when users push the boundaries of cache and directory > size > (google telldir+horror). Shardmap avoids this issue entirely by > storing > and traversing directory entries in simple, classic linear order. > > This touches on the single most significant difference between > Shardmap > and HTree: Shardmap strictly separates its index from record entry > blocks, > while HTree embeds entries directly in the BTree index. The HTree > strategy performs impressively well at low to medium directory > scales, > but at higher scales it causes significantly more cache pressure, due > to > the fact that the cache footprint of any randomly accessed index is > necessarily the entire index. In contrast, Shardmap stores directory > entries permanently in creation order, so that directory traversal is > in simple linear order with effectively zero overhead. This avoids > perhaps HTree's most dubious design feature, its arcane and not > completely > reliable hash order readdir traversal, which miraculously has avoided > serious meltdown over these past two decades due to a legendary hack > by > Ted and subsequent careful adaptation to handle various corner cases. > Nowhere in Shardmap will you find any such arcane and marginally > supportable code, which should be a great relief to Ext4 maintainers. > Or to put it another way, if somebody out there wishes to export a > billion file directory using NFSv2, Shardmap will not be the reason > why that does not work whereas HTree most probably would be. > > Besides separating out the index from entry records and accessing > those > records linearly in most situations, Shardmap also benefits from a > very > compact index design. Even if a directory has a billion entries, each > index entry is only eight bytes in size. This exercise in structure > compaction proved possible because the number of hash bits needed for > the > hash code decreases as the number of index shards increases, freeing > up > bits for larger block numbers as the directory expands. Shardmap > therefore implements an index entry as several variable sized fields. > This strategy works well up to the billion entry range, above which > the > number of hash index collisions (each of which must be resolved by > accessing an underlying record block) starts to increase noticeably. > This is really the only factor that limits Shardmap performance above > a billion entries. Should we wish Shardmap to scale to trillions of > entries without losing performance, we will need to increase the > index > entry size to ten bytes or so, or come up with some as yet unknown > clever improvement (potential thesis project goes here). > > There are many additional technical details of Shardmap that ought to > be > explained, however today my primary purpose is simply to introduce > what > I view as a compelling case for obsoleting HTree. To that end, fewer > words are better and this post is already quite long enough. I would > love > to get into some other interesting details, for example, the Bigmap > free > space mapping strategy, but that really needs its own post to do it > justice, as do a number of other subjects. > > Wrapping up, what about that theoretical case where HTree outperforms > Shardmap? This is theoretical because one needs to operate on a huge > directory with tiny cache to trigger it. Both Shardmap and HTree will > exhibit read multiplication under such conditions, due to frequent > cache evictions, however the Shardmap read multiplication will be > many > times higher than HTree because of its coarser cache granularity. In > the > unlikely event that we ever need to fix this, one viable solution is > to > add paging support for Shardmap's in-memory cache structure, a > standard > technique sometimes called "anticache". > > That is it for today. There remains much to explain about Shardmap > both > within and beyond the Ext4 context. For example, Shardmap has proved > to > work very well as a standalone key value store, particularly with > persistent memory. In fact, we have benchmarked Shardmap at over > three > million atomic, durable database operations per second on an Intel > Optane server, which might well be a new world record. The details of > how this was done are fascinating, however this post is far too small > to > contain them today. Perhaps this should be thing 1(b) for next week. > Let's imagine that it needs to implement the Shardmap approach. Could you estimate the implementation and stabilization time? How expensive and long-term efforts could it be? Thanks, Viacheslav Dubeyko.
