#include"bcachefs.h" #include"bkey.h" #include"bkey_methods.h" #include"btree_types.h" #include"util.h"/* for time_stats */ #include"vstructs.h"
/* * BKEYS: * * A bkey contains a key, a size field, a variable number of pointers, and some * ancillary flag bits. * * We use two different functions for validating bkeys, bkey_invalid and * bkey_deleted(). * * The one exception to the rule that ptr_invalid() filters out invalid keys is * that it also filters out keys of size 0 - these are keys that have been * completely overwritten. It'd be safe to delete these in memory while leaving * them on disk, just unnecessary work - so we filter them out when resorting * instead. * * We can't filter out stale keys when we're resorting, because garbage * collection needs to find them to ensure bucket gens don't wrap around - * unless we're rewriting the btree node those stale keys still exist on disk. * * We also implement functions here for removing some number of sectors from the * front or the back of a bkey - this is mainly used for fixing overlapping * extents, by removing the overlapping sectors from the older key. * * BSETS: * * A bset is an array of bkeys laid out contiguously in memory in sorted order, * along with a header. A btree node is made up of a number of these, written at * different times. * * There could be many of them on disk, but we never allow there to be more than * 4 in memory - we lazily resort as needed. * * We implement code here for creating and maintaining auxiliary search trees * (described below) for searching an individial bset, and on top of that we * implement a btree iterator. * * BTREE ITERATOR: * * Most of the code in bcache doesn't care about an individual bset - it needs * to search entire btree nodes and iterate over them in sorted order. * * The btree iterator code serves both functions; it iterates through the keys * in a btree node in sorted order, starting from either keys after a specific * point (if you pass it a search key) or the start of the btree node. * * AUXILIARY SEARCH TREES: * * Since keys are variable length, we can't use a binary search on a bset - we * wouldn't be able to find the start of the next key. But binary searches are * slow anyways, due to terrible cache behaviour; bcache originally used binary * searches and that code topped out at under 50k lookups/second. * * So we need to construct some sort of lookup table. Since we only insert keys * into the last (unwritten) set, most of the keys within a given btree node are * usually in sets that are mostly constant. We use two different types of * lookup tables to take advantage of this. * * Both lookup tables share in common that they don't index every key in the * set; they index one key every BSET_CACHELINE bytes, and then a linear search * is used for the rest. * * For sets that have been written to disk and are no longer being inserted * into, we construct a binary search tree in an array - traversing a binary * search tree in an array gives excellent locality of reference and is very * fast, since both children of any node are adjacent to each other in memory * (and their grandchildren, and great grandchildren...) - this means * prefetching can be used to great effect. * * It's quite useful performance wise to keep these nodes small - not just * because they're more likely to be in L2, but also because we can prefetch * more nodes on a single cacheline and thus prefetch more iterations in advance * when traversing this tree. * * Nodes in the auxiliary search tree must contain both a key to compare against * (we don't want to fetch the key from the set, that would defeat the purpose), * and a pointer to the key. We use a few tricks to compress both of these. * * To compress the pointer, we take advantage of the fact that one node in the * search tree corresponds to precisely BSET_CACHELINE bytes in the set. We have * a function (to_inorder()) that takes the index of a node in a binary tree and * returns what its index would be in an inorder traversal, so we only have to * store the low bits of the offset. * * The key is 84 bits (KEY_DEV + key->key, the offset on the device). To * compress that, we take advantage of the fact that when we're traversing the * search tree at every iteration we know that both our search key and the key * we're looking for lie within some range - bounded by our previous * comparisons. (We special case the start of a search so that this is true even * at the root of the tree). * * So we know the key we're looking for is between a and b, and a and b don't * differ higher than bit 50, we don't need to check anything higher than bit * 50. * * We don't usually need the rest of the bits, either; we only need enough bits * to partition the key range we're currently checking. Consider key n - the * key our auxiliary search tree node corresponds to, and key p, the key * immediately preceding n. The lowest bit we need to store in the auxiliary * search tree is the highest bit that differs between n and p. * * Note that this could be bit 0 - we might sometimes need all 80 bits to do the * comparison. But we'd really like our nodes in the auxiliary search tree to be * of fixed size. * * The solution is to make them fixed size, and when we're constructing a node * check if p and n differed in the bits we needed them to. If they don't we * flag that node, and when doing lookups we fallback to comparing against the * real key. As long as this doesn't happen to often (and it seems to reliably * happen a bit less than 1% of the time), we win - even on failures, that key * is then more likely to be in cache than if we were doing binary searches all * the way, since we're touching so much less memory. * * The keys in the auxiliary search tree are stored in (software) floating * point, with an exponent and a mantissa. The exponent needs to be big enough * to address all the bits in the original key, but the number of bits in the * mantissa is somewhat arbitrary; more bits just gets us fewer failures. * * We need 7 bits for the exponent and 3 bits for the key's offset (since keys * are 8 byte aligned); using 22 bits for the mantissa means a node is 4 bytes. * We need one node per 128 bytes in the btree node, which means the auxiliary * search trees take up 3% as much memory as the btree itself. * * Constructing these auxiliary search trees is moderately expensive, and we * don't want to be constantly rebuilding the search tree for the last set * whenever we insert another key into it. For the unwritten set, we use a much * simpler lookup table - it's just a flat array, so index i in the lookup table * corresponds to the i range of BSET_CACHELINE bytes in the set. Indexing * within each byte range works the same as with the auxiliary search trees. * * These are much easier to keep up to date when we insert a key - we do it * somewhat lazily; when we shift a key up we usually just increment the pointer * to it, only when it would overflow do we go to the trouble of finding the * first key in that range of bytes again.
*/
/* * BSET_CACHELINE was originally intended to match the hardware cacheline size - * it used to be 64, but I realized the lookup code would touch slightly less * memory if it was 128. * * It definites the number of bytes (in struct bset) per struct bkey_float in * the auxiliar search tree - when we're done searching the bset_float tree we * have this many bytes left that we do a linear search over. * * Since (after level 5) every level of the bset_tree is on a new cacheline, * we're touching one fewer cacheline in the bset tree in exchange for one more * cacheline in the linear search - but the linear search might stop before it * gets to the second cacheline.
*/
/* * When keys compare equal, deleted keys compare first: * * XXX: only need to compare pointers for keys that are both within a * btree_node_iterator - we need to break ties for prev() to work correctly
*/ staticinlineint bkey_iter_cmp(conststruct btree *b, conststruct bkey_packed *l, conststruct bkey_packed *r)
{ return bch2_bkey_cmp_packed(b, l, r)
?: (int) bkey_deleted(r) - (int) bkey_deleted(l)
?: cmp_int(l, r);
}
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