linux/net/ceph/crush/mapper.c

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/*
* Ceph - scalable distributed file system
*
* Copyright (C) 2015 Intel Corporation All Rights Reserved
*
* This is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License version 2.1, as published by the Free Software
* Foundation. See file COPYING.
*
*/
#ifdef __KERNEL__
# include <linux/string.h>
# include <linux/slab.h>
# include <linux/bug.h>
# include <linux/kernel.h>
# include <linux/crush/crush.h>
# include <linux/crush/hash.h>
# include <linux/crush/mapper.h>
#else
# include "crush_compat.h"
# include "crush.h"
# include "hash.h"
# include "mapper.h"
#endif
#include "crush_ln_table.h"
#define dprintk(args...) /* printf(args) */
/*
* Implement the core CRUSH mapping algorithm.
*/
/**
* crush_find_rule - find a crush_rule id for a given ruleset, type, and size.
* @map: the crush_map
* @ruleset: the storage ruleset id (user defined)
* @type: storage ruleset type (user defined)
* @size: output set size
*/
int crush_find_rule(const struct crush_map *map, int ruleset, int type, int size)
{
__u32 i;
for (i = 0; i < map->max_rules; i++) {
if (map->rules[i] &&
map->rules[i]->mask.ruleset == ruleset &&
map->rules[i]->mask.type == type &&
map->rules[i]->mask.min_size <= size &&
map->rules[i]->mask.max_size >= size)
return i;
}
return -1;
}
/*
* bucket choose methods
*
* For each bucket algorithm, we have a "choose" method that, given a
* crush input @x and replica position (usually, position in output set) @r,
* will produce an item in the bucket.
*/
/*
* Choose based on a random permutation of the bucket.
*
* We used to use some prime number arithmetic to do this, but it
* wasn't very random, and had some other bad behaviors. Instead, we
* calculate an actual random permutation of the bucket members.
* Since this is expensive, we optimize for the r=0 case, which
* captures the vast majority of calls.
*/
static int bucket_perm_choose(const struct crush_bucket *bucket,
struct crush_work_bucket *work,
int x, int r)
{
unsigned int pr = r % bucket->size;
unsigned int i, s;
/* start a new permutation if @x has changed */
if (work->perm_x != (__u32)x || work->perm_n == 0) {
dprintk("bucket %d new x=%d\n", bucket->id, x);
work->perm_x = x;
/* optimize common r=0 case */
if (pr == 0) {
s = crush_hash32_3(bucket->hash, x, bucket->id, 0) %
bucket->size;
work->perm[0] = s;
work->perm_n = 0xffff; /* magic value, see below */
goto out;
}
for (i = 0; i < bucket->size; i++)
work->perm[i] = i;
work->perm_n = 0;
} else if (work->perm_n == 0xffff) {
/* clean up after the r=0 case above */
for (i = 1; i < bucket->size; i++)
work->perm[i] = i;
work->perm[work->perm[0]] = 0;
work->perm_n = 1;
}
/* calculate permutation up to pr */
for (i = 0; i < work->perm_n; i++)
dprintk(" perm_choose have %d: %d\n", i, work->perm[i]);
while (work->perm_n <= pr) {
unsigned int p = work->perm_n;
/* no point in swapping the final entry */
if (p < bucket->size - 1) {
i = crush_hash32_3(bucket->hash, x, bucket->id, p) %
(bucket->size - p);
if (i) {
unsigned int t = work->perm[p + i];
work->perm[p + i] = work->perm[p];
work->perm[p] = t;
}
dprintk(" perm_choose swap %d with %d\n", p, p+i);
}
work->perm_n++;
}
for (i = 0; i < bucket->size; i++)
dprintk(" perm_choose %d: %d\n", i, work->perm[i]);
s = work->perm[pr];
out:
dprintk(" perm_choose %d sz=%d x=%d r=%d (%d) s=%d\n", bucket->id,
bucket->size, x, r, pr, s);
return bucket->items[s];
}
/* uniform */
static int bucket_uniform_choose(const struct crush_bucket_uniform *bucket,
struct crush_work_bucket *work, int x, int r)
{
return bucket_perm_choose(&bucket->h, work, x, r);
}
/* list */
static int bucket_list_choose(const struct crush_bucket_list *bucket,
int x, int r)
{
int i;
for (i = bucket->h.size-1; i >= 0; i--) {
__u64 w = crush_hash32_4(bucket->h.hash, x, bucket->h.items[i],
r, bucket->h.id);
w &= 0xffff;
dprintk("list_choose i=%d x=%d r=%d item %d weight %x "
"sw %x rand %llx",
i, x, r, bucket->h.items[i], bucket->item_weights[i],
bucket->sum_weights[i], w);
w *= bucket->sum_weights[i];
w = w >> 16;
/*dprintk(" scaled %llx\n", w);*/
if (w < bucket->item_weights[i]) {
return bucket->h.items[i];
}
}
dprintk("bad list sums for bucket %d\n", bucket->h.id);
return bucket->h.items[0];
}
/* (binary) tree */
static int height(int n)
{
int h = 0;
while ((n & 1) == 0) {
h++;
n = n >> 1;
}
return h;
}
static int left(int x)
{
int h = height(x);
return x - (1 << (h-1));
}
static int right(int x)
{
int h = height(x);
return x + (1 << (h-1));
}
static int terminal(int x)
{
return x & 1;
}
static int bucket_tree_choose(const struct crush_bucket_tree *bucket,
int x, int r)
{
int n;
__u32 w;
__u64 t;
/* start at root */
n = bucket->num_nodes >> 1;
while (!terminal(n)) {
int l;
/* pick point in [0, w) */
w = bucket->node_weights[n];
t = (__u64)crush_hash32_4(bucket->h.hash, x, n, r,
bucket->h.id) * (__u64)w;
t = t >> 32;
/* descend to the left or right? */
l = left(n);
if (t < bucket->node_weights[l])
n = l;
else
n = right(n);
}
return bucket->h.items[n >> 1];
}
/* straw */
static int bucket_straw_choose(const struct crush_bucket_straw *bucket,
int x, int r)
{
__u32 i;
int high = 0;
__u64 high_draw = 0;
__u64 draw;
for (i = 0; i < bucket->h.size; i++) {
draw = crush_hash32_3(bucket->h.hash, x, bucket->h.items[i], r);
draw &= 0xffff;
draw *= bucket->straws[i];
if (i == 0 || draw > high_draw) {
high = i;
high_draw = draw;
}
}
return bucket->h.items[high];
}
/* compute 2^44*log2(input+1) */
static __u64 crush_ln(unsigned int xin)
{
unsigned int x = xin;
int iexpon, index1, index2;
__u64 RH, LH, LL, xl64, result;
x++;
/* normalize input */
iexpon = 15;
/*
* figure out number of bits we need to shift and
* do it in one step instead of iteratively
*/
if (!(x & 0x18000)) {
int bits = __builtin_clz(x & 0x1FFFF) - 16;
x <<= bits;
iexpon = 15 - bits;
}
index1 = (x >> 8) << 1;
/* RH ~ 2^56/index1 */
RH = __RH_LH_tbl[index1 - 256];
/* LH ~ 2^48 * log2(index1/256) */
LH = __RH_LH_tbl[index1 + 1 - 256];
/* RH*x ~ 2^48 * (2^15 + xf), xf<2^8 */
xl64 = (__s64)x * RH;
xl64 >>= 48;
result = iexpon;
result <<= (12 + 32);
index2 = xl64 & 0xff;
/* LL ~ 2^48*log2(1.0+index2/2^15) */
LL = __LL_tbl[index2];
LH = LH + LL;
LH >>= (48 - 12 - 32);
result += LH;
return result;
}
/*
* straw2
*
* for reference, see:
*
* http://en.wikipedia.org/wiki/Exponential_distribution#Distribution_of_the_minimum_of_exponential_random_variables
*
*/
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
static __u32 *get_choose_arg_weights(const struct crush_bucket_straw2 *bucket,
const struct crush_choose_arg *arg,
int position)
{
if (!arg || !arg->weight_set)
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
return bucket->item_weights;
if (position >= arg->weight_set_size)
position = arg->weight_set_size - 1;
return arg->weight_set[position].weights;
}
static __s32 *get_choose_arg_ids(const struct crush_bucket_straw2 *bucket,
const struct crush_choose_arg *arg)
{
if (!arg || !arg->ids)
return bucket->h.items;
return arg->ids;
}
static int bucket_straw2_choose(const struct crush_bucket_straw2 *bucket,
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
int x, int r,
const struct crush_choose_arg *arg,
int position)
{
unsigned int i, high = 0;
unsigned int u;
__s64 ln, draw, high_draw = 0;
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
__u32 *weights = get_choose_arg_weights(bucket, arg, position);
__s32 *ids = get_choose_arg_ids(bucket, arg);
for (i = 0; i < bucket->h.size; i++) {
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
dprintk("weight 0x%x item %d\n", weights[i], ids[i]);
if (weights[i]) {
u = crush_hash32_3(bucket->h.hash, x, ids[i], r);
u &= 0xffff;
/*
* for some reason slightly less than 0x10000 produces
* a slightly more accurate distribution... probably a
* rounding effect.
*
* the natural log lookup table maps [0,0xffff]
* (corresponding to real numbers [1/0x10000, 1] to
* [0, 0xffffffffffff] (corresponding to real numbers
* [-11.090355,0]).
*/
ln = crush_ln(u) - 0x1000000000000ll;
/*
* divide by 16.16 fixed-point weight. note
* that the ln value is negative, so a larger
* weight means a larger (less negative) value
* for draw.
*/
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
draw = div64_s64(ln, weights[i]);
} else {
draw = S64_MIN;
}
if (i == 0 || draw > high_draw) {
high = i;
high_draw = draw;
}
}
return bucket->h.items[high];
}
static int crush_bucket_choose(const struct crush_bucket *in,
struct crush_work_bucket *work,
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
int x, int r,
const struct crush_choose_arg *arg,
int position)
{
dprintk(" crush_bucket_choose %d x=%d r=%d\n", in->id, x, r);
BUG_ON(in->size == 0);
switch (in->alg) {
case CRUSH_BUCKET_UNIFORM:
return bucket_uniform_choose(
(const struct crush_bucket_uniform *)in,
work, x, r);
case CRUSH_BUCKET_LIST:
return bucket_list_choose((const struct crush_bucket_list *)in,
x, r);
case CRUSH_BUCKET_TREE:
return bucket_tree_choose((const struct crush_bucket_tree *)in,
x, r);
case CRUSH_BUCKET_STRAW:
return bucket_straw_choose(
(const struct crush_bucket_straw *)in,
x, r);
case CRUSH_BUCKET_STRAW2:
return bucket_straw2_choose(
(const struct crush_bucket_straw2 *)in,
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
x, r, arg, position);
default:
dprintk("unknown bucket %d alg %d\n", in->id, in->alg);
return in->items[0];
}
}
/*
* true if device is marked "out" (failed, fully offloaded)
* of the cluster
*/
static int is_out(const struct crush_map *map,
const __u32 *weight, int weight_max,
int item, int x)
{
if (item >= weight_max)
return 1;
if (weight[item] >= 0x10000)
return 0;
if (weight[item] == 0)
return 1;
if ((crush_hash32_2(CRUSH_HASH_RJENKINS1, x, item) & 0xffff)
< weight[item])
return 0;
return 1;
}
/**
* crush_choose_firstn - choose numrep distinct items of given type
* @map: the crush_map
* @bucket: the bucket we are choose an item from
* @x: crush input value
* @numrep: the number of items to choose
* @type: the type of item to choose
* @out: pointer to output vector
* @outpos: our position in that vector
* @out_size: size of the out vector
* @tries: number of attempts to make
* @recurse_tries: number of attempts to have recursive chooseleaf make
* @local_retries: localized retries
* @local_fallback_retries: localized fallback retries
* @recurse_to_leaf: true if we want one device under each item of given type (chooseleaf instead of choose)
* @stable: stable mode starts rep=0 in the recursive call for all replicas
* @vary_r: pass r to recursive calls
* @out2: second output vector for leaf items (if @recurse_to_leaf)
* @parent_r: r value passed from the parent
*/
static int crush_choose_firstn(const struct crush_map *map,
struct crush_work *work,
const struct crush_bucket *bucket,
const __u32 *weight, int weight_max,
int x, int numrep, int type,
int *out, int outpos,
int out_size,
unsigned int tries,
unsigned int recurse_tries,
unsigned int local_retries,
unsigned int local_fallback_retries,
int recurse_to_leaf,
unsigned int vary_r,
unsigned int stable,
int *out2,
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
int parent_r,
const struct crush_choose_arg *choose_args)
{
int rep;
unsigned int ftotal, flocal;
int retry_descent, retry_bucket, skip_rep;
const struct crush_bucket *in = bucket;
int r;
int i;
int item = 0;
int itemtype;
int collide, reject;
int count = out_size;
dprintk("CHOOSE%s bucket %d x %d outpos %d numrep %d tries %d recurse_tries %d local_retries %d local_fallback_retries %d parent_r %d stable %d\n",
recurse_to_leaf ? "_LEAF" : "",
bucket->id, x, outpos, numrep,
tries, recurse_tries, local_retries, local_fallback_retries,
parent_r, stable);
for (rep = stable ? 0 : outpos; rep < numrep && count > 0 ; rep++) {
/* keep trying until we get a non-out, non-colliding item */
ftotal = 0;
skip_rep = 0;
do {
retry_descent = 0;
in = bucket; /* initial bucket */
/* choose through intervening buckets */
flocal = 0;
do {
collide = 0;
retry_bucket = 0;
r = rep + parent_r;
/* r' = r + f_total */
r += ftotal;
/* bucket choose */
if (in->size == 0) {
reject = 1;
goto reject;
}
if (local_fallback_retries > 0 &&
flocal >= (in->size>>1) &&
flocal > local_fallback_retries)
item = bucket_perm_choose(
in, work->work[-1-in->id],
x, r);
else
item = crush_bucket_choose(
in, work->work[-1-in->id],
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
x, r,
(choose_args ?
&choose_args[-1-in->id] : 0),
outpos);
if (item >= map->max_devices) {
dprintk(" bad item %d\n", item);
skip_rep = 1;
break;
}
/* desired type? */
if (item < 0)
itemtype = map->buckets[-1-item]->type;
else
itemtype = 0;
dprintk(" item %d type %d\n", item, itemtype);
/* keep going? */
if (itemtype != type) {
if (item >= 0 ||
(-1-item) >= map->max_buckets) {
dprintk(" bad item type %d\n", type);
skip_rep = 1;
break;
}
in = map->buckets[-1-item];
retry_bucket = 1;
continue;
}
/* collision? */
for (i = 0; i < outpos; i++) {
if (out[i] == item) {
collide = 1;
break;
}
}
reject = 0;
if (!collide && recurse_to_leaf) {
if (item < 0) {
int sub_r;
if (vary_r)
sub_r = r >> (vary_r-1);
else
sub_r = 0;
if (crush_choose_firstn(
map,
work,
map->buckets[-1-item],
weight, weight_max,
x, stable ? 1 : outpos+1, 0,
out2, outpos, count,
recurse_tries, 0,
local_retries,
local_fallback_retries,
0,
vary_r,
stable,
NULL,
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
sub_r,
choose_args) <= outpos)
/* didn't get leaf */
reject = 1;
} else {
/* we already have a leaf! */
out2[outpos] = item;
}
}
if (!reject && !collide) {
/* out? */
if (itemtype == 0)
reject = is_out(map, weight,
weight_max,
item, x);
}
reject:
if (reject || collide) {
ftotal++;
flocal++;
if (collide && flocal <= local_retries)
/* retry locally a few times */
retry_bucket = 1;
else if (local_fallback_retries > 0 &&
flocal <= in->size + local_fallback_retries)
/* exhaustive bucket search */
retry_bucket = 1;
else if (ftotal < tries)
/* then retry descent */
retry_descent = 1;
else
/* else give up */
skip_rep = 1;
dprintk(" reject %d collide %d "
"ftotal %u flocal %u\n",
reject, collide, ftotal,
flocal);
}
} while (retry_bucket);
} while (retry_descent);
if (skip_rep) {
dprintk("skip rep\n");
continue;
}
dprintk("CHOOSE got %d\n", item);
out[outpos] = item;
outpos++;
count--;
#ifndef __KERNEL__
if (map->choose_tries && ftotal <= map->choose_total_tries)
map->choose_tries[ftotal]++;
#endif
}
dprintk("CHOOSE returns %d\n", outpos);
return outpos;
}
/**
* crush_choose_indep: alternative breadth-first positionally stable mapping
*
*/
static void crush_choose_indep(const struct crush_map *map,
struct crush_work *work,
const struct crush_bucket *bucket,
const __u32 *weight, int weight_max,
int x, int left, int numrep, int type,
int *out, int outpos,
unsigned int tries,
unsigned int recurse_tries,
int recurse_to_leaf,
int *out2,
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
int parent_r,
const struct crush_choose_arg *choose_args)
{
const struct crush_bucket *in = bucket;
int endpos = outpos + left;
int rep;
unsigned int ftotal;
int r;
int i;
int item = 0;
int itemtype;
int collide;
dprintk("CHOOSE%s INDEP bucket %d x %d outpos %d numrep %d\n", recurse_to_leaf ? "_LEAF" : "",
bucket->id, x, outpos, numrep);
/* initially my result is undefined */
for (rep = outpos; rep < endpos; rep++) {
out[rep] = CRUSH_ITEM_UNDEF;
if (out2)
out2[rep] = CRUSH_ITEM_UNDEF;
}
for (ftotal = 0; left > 0 && ftotal < tries; ftotal++) {
#ifdef DEBUG_INDEP
if (out2 && ftotal) {
dprintk("%u %d a: ", ftotal, left);
for (rep = outpos; rep < endpos; rep++) {
dprintk(" %d", out[rep]);
}
dprintk("\n");
dprintk("%u %d b: ", ftotal, left);
for (rep = outpos; rep < endpos; rep++) {
dprintk(" %d", out2[rep]);
}
dprintk("\n");
}
#endif
for (rep = outpos; rep < endpos; rep++) {
if (out[rep] != CRUSH_ITEM_UNDEF)
continue;
in = bucket; /* initial bucket */
/* choose through intervening buckets */
for (;;) {
/* note: we base the choice on the position
* even in the nested call. that means that
* if the first layer chooses the same bucket
* in a different position, we will tend to
* choose a different item in that bucket.
* this will involve more devices in data
* movement and tend to distribute the load.
*/
r = rep + parent_r;
/* be careful */
if (in->alg == CRUSH_BUCKET_UNIFORM &&
in->size % numrep == 0)
/* r'=r+(n+1)*f_total */
r += (numrep+1) * ftotal;
else
/* r' = r + n*f_total */
r += numrep * ftotal;
/* bucket choose */
if (in->size == 0) {
dprintk(" empty bucket\n");
break;
}
item = crush_bucket_choose(
in, work->work[-1-in->id],
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
x, r,
(choose_args ?
&choose_args[-1-in->id] : 0),
outpos);
if (item >= map->max_devices) {
dprintk(" bad item %d\n", item);
out[rep] = CRUSH_ITEM_NONE;
if (out2)
out2[rep] = CRUSH_ITEM_NONE;
left--;
break;
}
/* desired type? */
if (item < 0)
itemtype = map->buckets[-1-item]->type;
else
itemtype = 0;
dprintk(" item %d type %d\n", item, itemtype);
/* keep going? */
if (itemtype != type) {
if (item >= 0 ||
(-1-item) >= map->max_buckets) {
dprintk(" bad item type %d\n", type);
out[rep] = CRUSH_ITEM_NONE;
if (out2)
out2[rep] =
CRUSH_ITEM_NONE;
left--;
break;
}
in = map->buckets[-1-item];
continue;
}
/* collision? */
collide = 0;
for (i = outpos; i < endpos; i++) {
if (out[i] == item) {
collide = 1;
break;
}
}
if (collide)
break;
if (recurse_to_leaf) {
if (item < 0) {
crush_choose_indep(
map,
work,
map->buckets[-1-item],
weight, weight_max,
x, 1, numrep, 0,
out2, rep,
recurse_tries, 0,
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
0, NULL, r,
choose_args);
if (out2[rep] == CRUSH_ITEM_NONE) {
/* placed nothing; no leaf */
break;
}
} else {
/* we already have a leaf! */
out2[rep] = item;
}
}
/* out? */
if (itemtype == 0 &&
is_out(map, weight, weight_max, item, x))
break;
/* yay! */
out[rep] = item;
left--;
break;
}
}
}
for (rep = outpos; rep < endpos; rep++) {
if (out[rep] == CRUSH_ITEM_UNDEF) {
out[rep] = CRUSH_ITEM_NONE;
}
if (out2 && out2[rep] == CRUSH_ITEM_UNDEF) {
out2[rep] = CRUSH_ITEM_NONE;
}
}
#ifndef __KERNEL__
if (map->choose_tries && ftotal <= map->choose_total_tries)
map->choose_tries[ftotal]++;
#endif
#ifdef DEBUG_INDEP
if (out2) {
dprintk("%u %d a: ", ftotal, left);
for (rep = outpos; rep < endpos; rep++) {
dprintk(" %d", out[rep]);
}
dprintk("\n");
dprintk("%u %d b: ", ftotal, left);
for (rep = outpos; rep < endpos; rep++) {
dprintk(" %d", out2[rep]);
}
dprintk("\n");
}
#endif
}
/*
* This takes a chunk of memory and sets it up to be a shiny new
* working area for a CRUSH placement computation. It must be called
* on any newly allocated memory before passing it in to
* crush_do_rule. It may be used repeatedly after that, so long as the
* map has not changed. If the map /has/ changed, you must make sure
* the working size is no smaller than what was allocated and re-run
* crush_init_workspace.
*
* If you do retain the working space between calls to crush, make it
* thread-local.
*/
void crush_init_workspace(const struct crush_map *map, void *v)
{
struct crush_work *w = v;
__s32 b;
/*
* We work by moving through the available space and setting
* values and pointers as we go.
*
* It's a bit like Forth's use of the 'allot' word since we
* set the pointer first and then reserve the space for it to
* point to by incrementing the point.
*/
v += sizeof(struct crush_work);
w->work = v;
v += map->max_buckets * sizeof(struct crush_work_bucket *);
for (b = 0; b < map->max_buckets; ++b) {
if (!map->buckets[b])
continue;
w->work[b] = v;
switch (map->buckets[b]->alg) {
default:
v += sizeof(struct crush_work_bucket);
break;
}
w->work[b]->perm_x = 0;
w->work[b]->perm_n = 0;
w->work[b]->perm = v;
v += map->buckets[b]->size * sizeof(__u32);
}
BUG_ON(v - (void *)w != map->working_size);
}
/**
* crush_do_rule - calculate a mapping with the given input and rule
* @map: the crush_map
* @ruleno: the rule id
* @x: hash input
* @result: pointer to result vector
* @result_max: maximum result size
* @weight: weight vector (for map leaves)
* @weight_max: size of weight vector
* @cwin: pointer to at least crush_work_size() bytes of memory
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
* @choose_args: weights and ids for each known bucket
*/
int crush_do_rule(const struct crush_map *map,
int ruleno, int x, int *result, int result_max,
const __u32 *weight, int weight_max,
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
void *cwin, const struct crush_choose_arg *choose_args)
{
int result_len;
struct crush_work *cw = cwin;
int *a = cwin + map->working_size;
int *b = a + result_max;
int *c = b + result_max;
int *w = a;
int *o = b;
int recurse_to_leaf;
int wsize = 0;
int osize;
int *tmp;
const struct crush_rule *rule;
__u32 step;
int i, j;
int numrep;
int out_size;
/*
* the original choose_total_tries value was off by one (it
* counted "retries" and not "tries"). add one.
*/
int choose_tries = map->choose_total_tries + 1;
int choose_leaf_tries = 0;
/*
* the local tries values were counted as "retries", though,
* and need no adjustment
*/
int choose_local_retries = map->choose_local_tries;
int choose_local_fallback_retries = map->choose_local_fallback_tries;
int vary_r = map->chooseleaf_vary_r;
int stable = map->chooseleaf_stable;
if ((__u32)ruleno >= map->max_rules) {
dprintk(" bad ruleno %d\n", ruleno);
return 0;
}
rule = map->rules[ruleno];
result_len = 0;
for (step = 0; step < rule->len; step++) {
int firstn = 0;
const struct crush_rule_step *curstep = &rule->steps[step];
switch (curstep->op) {
case CRUSH_RULE_TAKE:
if ((curstep->arg1 >= 0 &&
curstep->arg1 < map->max_devices) ||
(-1-curstep->arg1 >= 0 &&
-1-curstep->arg1 < map->max_buckets &&
map->buckets[-1-curstep->arg1])) {
w[0] = curstep->arg1;
wsize = 1;
} else {
dprintk(" bad take value %d\n", curstep->arg1);
}
break;
case CRUSH_RULE_SET_CHOOSE_TRIES:
if (curstep->arg1 > 0)
choose_tries = curstep->arg1;
break;
case CRUSH_RULE_SET_CHOOSELEAF_TRIES:
if (curstep->arg1 > 0)
choose_leaf_tries = curstep->arg1;
break;
case CRUSH_RULE_SET_CHOOSE_LOCAL_TRIES:
if (curstep->arg1 >= 0)
choose_local_retries = curstep->arg1;
break;
case CRUSH_RULE_SET_CHOOSE_LOCAL_FALLBACK_TRIES:
if (curstep->arg1 >= 0)
choose_local_fallback_retries = curstep->arg1;
break;
case CRUSH_RULE_SET_CHOOSELEAF_VARY_R:
if (curstep->arg1 >= 0)
vary_r = curstep->arg1;
break;
case CRUSH_RULE_SET_CHOOSELEAF_STABLE:
if (curstep->arg1 >= 0)
stable = curstep->arg1;
break;
case CRUSH_RULE_CHOOSELEAF_FIRSTN:
case CRUSH_RULE_CHOOSE_FIRSTN:
firstn = 1;
/* fall through */
case CRUSH_RULE_CHOOSELEAF_INDEP:
case CRUSH_RULE_CHOOSE_INDEP:
if (wsize == 0)
break;
recurse_to_leaf =
curstep->op ==
CRUSH_RULE_CHOOSELEAF_FIRSTN ||
curstep->op ==
CRUSH_RULE_CHOOSELEAF_INDEP;
/* reset output */
osize = 0;
for (i = 0; i < wsize; i++) {
int bno;
numrep = curstep->arg1;
if (numrep <= 0) {
numrep += result_max;
if (numrep <= 0)
continue;
}
j = 0;
/* make sure bucket id is valid */
bno = -1 - w[i];
if (bno < 0 || bno >= map->max_buckets) {
/* w[i] is probably CRUSH_ITEM_NONE */
dprintk(" bad w[i] %d\n", w[i]);
continue;
}
if (firstn) {
int recurse_tries;
if (choose_leaf_tries)
recurse_tries =
choose_leaf_tries;
else if (map->chooseleaf_descend_once)
recurse_tries = 1;
else
recurse_tries = choose_tries;
osize += crush_choose_firstn(
map,
cw,
map->buckets[bno],
weight, weight_max,
x, numrep,
curstep->arg2,
o+osize, j,
result_max-osize,
choose_tries,
recurse_tries,
choose_local_retries,
choose_local_fallback_retries,
recurse_to_leaf,
vary_r,
stable,
c+osize,
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
0,
choose_args);
} else {
out_size = ((numrep < (result_max-osize)) ?
numrep : (result_max-osize));
crush_choose_indep(
map,
cw,
map->buckets[bno],
weight, weight_max,
x, out_size, numrep,
curstep->arg2,
o+osize, j,
choose_tries,
choose_leaf_tries ?
choose_leaf_tries : 1,
recurse_to_leaf,
c+osize,
crush: implement weight and id overrides for straw2 bucket_straw2_choose needs to use weights that may be different from weight_items. For instance to compensate for an uneven distribution caused by a low number of values. Or to fix the probability biais introduced by conditional probabilities (see http://tracker.ceph.com/issues/15653 for more information). We introduce a weight_set for each straw2 bucket to set the desired weight for a given item at a given position. The weight of a given item when picking the first replica (first position) may be different from the weight the second replica (second position). For instance the weight matrix for a given bucket containing items 3, 7 and 13 could be as follows: position 0 position 1 item 3 0x10000 0x100000 item 7 0x40000 0x10000 item 13 0x40000 0x10000 When crush_do_rule picks the first of two replicas (position 0), item 7, 3 are four times more likely to be choosen by bucket_straw2_choose than item 13. When choosing the second replica (position 1), item 3 is ten times more likely to be choosen than item 7, 13. By default the weight_set of each bucket exactly matches the content of item_weights for each position to ensure backward compatibility. bucket_straw2_choose compares items by using their id. The same ids are also used to index buckets and they must be unique. For each item in a bucket an array of ids can be provided for placement purposes and they are used instead of the ids. If no replacement ids are provided, the legacy behavior is preserved. Reflects ceph.git commit 19537a450fd5c5a0bb8b7830947507a76db2ceca. Signed-off-by: Ilya Dryomov <idryomov@gmail.com>
2017-06-22 17:44:05 +00:00
0,
choose_args);
osize += out_size;
}
}
if (recurse_to_leaf)
/* copy final _leaf_ values to output set */
memcpy(o, c, osize*sizeof(*o));
/* swap o and w arrays */
tmp = o;
o = w;
w = tmp;
wsize = osize;
break;
case CRUSH_RULE_EMIT:
for (i = 0; i < wsize && result_len < result_max; i++) {
result[result_len] = w[i];
result_len++;
}
wsize = 0;
break;
default:
dprintk(" unknown op %d at step %d\n",
curstep->op, step);
break;
}
}
return result_len;
}