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Rewrite LPOptimizer.pm to nodejs

trace-sqes
Vitaliy Filippov 2020-05-06 02:08:15 +03:00
parent e8149e5848
commit 842f88f94f
2 changed files with 465 additions and 14 deletions
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25
lp/LPOptimizer.pm
View File

@ -147,29 +147,28 @@ sub optimize_change
my $intersect = {};
for my $pg_name (keys %$prev_weights)
{
my @pg = split /_/, substr($pg_name, 'pg_');
$intersect->{$pg[0].'::'} = $intersect->{':'.$pg[1].':'} = $intersect->{'::'.$pg[2]} = 1;
$intersect->{$pg[0].'::'.$pg[2]} = $intersect->{':'.$pg[1].':'.$pg[2]} = $intersect->{$pg[0].':'.$pg[1].':'} = 2;
my @pg = split /_/, substr($pg_name, 3);
$intersect->{$pg[0].'::'} = $intersect->{':'.$pg[1].':'} = $intersect->{'::'.$pg[2]} = 2;
$intersect->{$pg[0].'::'.$pg[2]} = $intersect->{':'.$pg[1].':'.$pg[2]} = $intersect->{$pg[0].':'.$pg[1].':'} = 1;
}
my $move_weights = {};
for my $pg (@$pgs)
{
$move_weights->{'pg_'.join('_', @$pg)} =
$intersect->{$pg->[0].'::'.$pg->[2]} || $intersect->{':'.$pg->[1].':'.$pg->[2]} || $intersect->{$pg->[0].':'.$pg->[1].':'} ||
$intersect->{$pg->[0].'::'} || $intersect->{':'.$pg->[1].':'} || $intersect->{'::'.$pg->[2]} ||
$intersect->{$pg->[0].'::'.$pg->[2]} || $intersect->{':'.$pg->[1].':'.$pg->[2]} || $intersect->{$pg->[0].':'.$pg->[1].':'} || 3;
3;
}
# Calculate total weight - old PG weights
my $pg_names = [ map { 'pg_'.join('_', @$_) } @$pgs ];
my $all_weights = { map { %$_ } values %$osd_tree };
my $tw = 0;
$tw += $all_weights->{$_} for keys %$all_weights;
$tw = $tw/3;
my $total_weight = 0;
$total_weight += $all_weights->{$_} for keys %$all_weights;
# Generate the LP problem
my $lp = "min: ".join(" + ", map { $move_weights->{$_} . ' * ' . ($prev_weights->{$_} ? "add_$_" : "$_") } @$pg_names).";\n";
$lp .= join(" + ", map { $prev_weights->{$_} ? "add_$_ - del_$_" : $_ } @$pg_names)." = 0;\n";
for my $osd (keys %$pg_per_osd)
{
my $w = $all_weights->{$osd};
my @s;
for my $pg (@{$pg_per_osd->{$osd}})
{
@ -182,7 +181,7 @@ sub optimize_change
push @s, $pg;
}
}
$lp .= join(" + ", @s)." <= ".int($all_weights->{$osd}/$tw*$pg_count - scalar(@{$prev_pg_per_osd->{$osd} || []})).";\n";
$lp .= join(" + ", @s)." <= ".int($all_weights->{$osd}*3/$total_weight*$pg_count - scalar(@{$prev_pg_per_osd->{$osd} || []})).";\n";
}
my @sec;
for my $pg (@$pg_names)
@ -225,8 +224,9 @@ sub optimize_change
for my $k (keys %$weights)
{
delete $weights->{$k} if !$weights->{$k};
print "$k: ".$weights->{$k}."\n" if $weights->{$k};
}
my $int_pgs = make_int_pgs($weights, scalar @$prev_int_pgs);
my $int_pgs = make_int_pgs($weights, $pg_count);
# Align them with most similar previous PGs
my $new_pgs = align_pgs($prev_int_pgs, $int_pgs);
my $differs = 0;
@ -245,9 +245,6 @@ sub optimize_change
}
}
}
my $eff = pg_list_space_efficiency($new_pgs, $osd_tree);
my $total_weight = 0;
$total_weight += $all_weights->{$_} for keys %$all_weights;
return {
prev_pgs => $prev_int_pgs,
score => $score,
@ -255,7 +252,7 @@ sub optimize_change
int_pgs => $new_pgs,
differs => $differs,
osd_differs => $osd_differs,
space => $eff,
space => pg_list_space_efficiency($new_pgs, $osd_tree),
total_space => $total_weight,
};
}

454
lp/lp-optimizer.js Normal file
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@ -0,0 +1,454 @@
// Data distribution optimizer using linear programming (lp_solve)
const child_process = require('child_process');
async function lp_solve(text)
{
const cp = child_process.spawn('lp_solve');
let stdout = '', stderr = '', finish_cb;
cp.stdout.on('data', buf => stdout += buf.toString());
cp.stderr.on('data', buf => stderr += buf.toString());
cp.on('exit', () => finish_cb && finish_cb());
cp.stdin.write(text);
cp.stdin.end();
if (cp.exitCode == null)
{
await new Promise(ok => finish_cb = ok);
}
let score = 0;
let vars = {};
for (const line of stdout.split(/\n/))
{
let m = /^(^Value of objective function: ([\d\.]+)|Actual values of the variables:)\s*$/.exec(line);
if (m)
{
if (m[2])
{
score = m[2];
}
continue;
}
else if (/This problem is infeasible/.exec(line))
{
return null;
}
let [ k, v ] = line.trim().split(/\s+/, 2);
if (v)
{
vars[k] = v;
}
}
return { score, vars };
}
function make_single(osd_tree)
{
const initial = all_combinations(osd_tree, 1)[0];
const all_weights = Object.assign.apply({}, Object.values(osd_tree));
let weight;
for (const osd of initial)
{
if (weight == null || all_weights[osd] < weight)
{
weight = all_weights[osd];
}
}
return [
{ set: initial, weight: weight },
];
}
async function optimize_initial(osd_tree, pg_count)
{
const all_weights = Object.assign.apply({}, Object.values(osd_tree));
const all_pgs = all_combinations($osd_tree);
const pg_per_osd = {};
for (const pg in all_pgs)
{
for (const osd of pg)
{
pg_per_osd[osd] = pg_per_osd[osd] || [];
pg_per_osd[osd].push("pg_"+pg.join("_"));
}
}
let lp = '';
lp += "max: "+all_pgs.map(pg => 'pg_'+pg.join('_')).join(' + ')+";\n";
for (const osd in pg_per_osd)
{
lp += pg_per_osd[osd].join(' + ')+' <= '+all_weights[osd]+';\n';
}
for (const pg of all_pgs)
{
lp += 'pg_'+pg.join('_')+" >= 0;\n";
}
lp += "int "+all_pgs.map(pg => 'pg_'+pg.join('_')).join(', ')+";\n";
const [ score, weights ] = await lp_solve(lp);
const int_pgs = make_int_pgs(weights, pg_count);
const eff = pg_list_space_efficiency(int_pgs, osd_tree);
const total_weight = Object.values(all_weights).reduce((a, c) => Number(a) + Number(c));
return { score, weights, int_pgs, total_space: eff*3, space_eff: eff*3/total_weight };
}
function make_int_pgs(weights, pg_count)
{
const total_weight = Object.values(weights).reduce((a, c) => Number(a) + Number(c));
let int_pgs = [];
let pg_left = pg_count;
let weight_left = total_weight;
for (const pg_name in weights)
{
let n = Math.round(weights[pg_name] / weight_left * pg_left);
for (let i = 0; i < n; i++)
{
int_pgs.push(pg_name.substr(3).split('_'));
}
weight_left -= weights[pg_name];
pg_left -= n;
}
return int_pgs;
}
function get_int_pg_weights(prev_int_pgs, osd_tree)
{
const space = pg_list_space_efficiency(prev_int_pgs, osd_tree);
const prev_weights = {};
let count = 0;
for (const pg of prev_int_pgs)
{
const pg_name = 'pg_'+pg.join('_');
prev_weights[pg_name] = (prev_weights[pg_name]||0) + 1;
count++;
}
for (const pg_name in prev_weights)
{
prev_weights[pg_name] *= space / count;
}
return prev_weights;
}
// Try to minimize data movement
async function optimize_change(prev_int_pgs, osd_tree)
{
const pg_count = prev_int_pgs.length;
const prev_weights = {};
const prev_pg_per_osd = {};
for (const pg of prev_int_pgs)
{
const pg_name = 'pg_'+pg.join('_');
prev_weights[pg_name] = (prev_weights[pg_name]||0) + 1;
for (const osd of pg)
{
prev_pg_per_osd[osd] = prev_pg_per_osd[osd] || [];
prev_pg_per_osd[osd].push(pg_name);
}
}
// Get all combinations
const all_pgs = all_combinations(osd_tree);
const pg_per_osd = {};
for (const pg of all_pgs)
{
const pg_name = 'pg_'+pg.join('_');
for (const osd of pg)
{
pg_per_osd[osd] = pg_per_osd[osd] || [];
pg_per_osd[osd].push(pg_name);
}
}
// Penalize PGs based on their similarity to old PGs
const intersect = {};
for (const pg_name in prev_weights)
{
const pg = pg_name.substr(3).split(/_/);
intersect[pg[0]+'::'] = intersect[':'+pg[1]+':'] = intersect['::'+pg[2]] = 2;
intersect[pg[0]+'::'+pg[2]] = intersect[':'+pg[1]+':'+pg[2]] = intersect[pg[0]+':'+pg[1]+':'] = 1;
}
const move_weights = {};
for (const pg of all_pgs)
{
move_weights['pg_'+pg.join('_')] =
intersect[pg[0]+'::'+pg[2]] || intersect[':'+pg[1]+':'+pg[2]] || intersect[pg[0]+':'+pg[1]+':'] ||
intersect[pg[0]+'::'] || intersect[':'+pg[1]+':'] || intersect['::'+pg[2]] ||
3;
}
// Calculate total weight - old PG weights
const all_pg_names = all_pgs.map(pg => 'pg_'+pg.join('_'));
const all_weights = Object.assign.apply({}, Object.values(osd_tree));
const total_weight = Object.values(all_weights).reduce((a, c) => Number(a) + Number(c));
// Generate the LP problem
let lp = '';
lp += 'min: '+all_pg_names.map(pg_name => move_weights[pg_name] + ' * ' + (prev_weights[pg_name] ? 'add_' : '') + pg_name).join(' + ')+';\n';
lp += all_pg_names.map(pg_name => prev_weights[pg_name] ? `add_${pg_name} - del_${pg_name}` : pg_name).join(' + ')+' = 0;\n';
for (const osd in pg_per_osd)
{
const osd_sum = (pg_per_osd[osd]||[]).map(pg_name => prev_weights[pg_name] ? `add_${pg_name} - del_${pg_name}` : pg_name).join(' + ');
const osd_weight = all_weights[osd]*3/total_weight*pg_count - (prev_pg_per_osd[osd]||[]).length;
lp += osd_sum + ' <= ' + Math.round(osd_weight) + ';\n';
}
let pg_vars = [];
for (const pg_name of all_pg_names)
{
if (prev_weights[pg_name])
{
pg_vars.push(`add_${pg_name}`, `del_${pg_name}`);
// Can't add or remove less than zero
lp += `add_${pg_name} >= 0;\n`;
lp += `del_${pg_name} >= 0;\n`;
// Can't remove more than the PG already has
lp += `add_${pg_name} - del_${pg_name} >= -${prev_weights[pg_name]};\n`;
}
else
{
pg_vars.push(pg_name);
lp += `${pg_name} >= 0;\n`;
}
}
lp += 'int '+pg_vars.join(', ')+';\n';
// Solve it
const lp_result = await lp_solve(lp);
if (!lp_result)
{
console.log(lp);
throw new Error('Problem is infeasible - is it a bug?');
}
// Generate the new distribution
const weights = { ...prev_weights };
for (const k in lp_result.vars)
{
if (k.substr(0, 4) === 'add_')
{
weights[k.substr(4)] = (weights[k.substr(4)] || 0) + Number(lp_result.vars[k]);
}
else if (k.substr(0, 4) === 'del_')
{
weights[k.substr(4)] = (weights[k.substr(4)] || 0) - Number(lp_result.vars[k]);
}
else
{
weights[k] = Number(lp_result.vars[k]);
}
}
for (const k in weights)
{
if (!weights[k])
{
delete weights[k];
}
}
const int_pgs = make_int_pgs(weights, pg_count);
// Align them with most similar previous PGs
const new_pgs = align_pgs(prev_int_pgs, int_pgs);
let differs = 0, osd_differs = 0;
for (let i = 0; i < pg_count; i++)
{
if (new_pgs[i].join('_') != prev_int_pgs[i].join('_'))
{
differs++;
}
for (let j = 0; j < 3; j++)
{
if (new_pgs[i][j] != prev_int_pgs[i][j])
{
osd_differs++;
}
}
}
return {
prev_pgs: prev_int_pgs,
score: lp_result.score,
weights,
int_pgs: new_pgs,
differs,
osd_differs,
space: pg_list_space_efficiency(new_pgs, osd_tree),
total_space: total_weight,
};
}
function print_change_stats(retval)
{
const new_pgs = retval.int_pgs;
const prev_int_pgs = retval.prev_pgs;
for (let i = 0; i < new_pgs.length; i++)
{
if (new_pgs[i].join('_') != prev_int_pgs[i].join('_'))
{
console.log("pg "+i+": "+prev_int_pgs[i].join(' ')+" -> "+new_pgs[i].join(' '));
}
}
console.log(
"Data movement: "+retval.differs+" pgs, "+
retval.osd_differs+" pg*osds = "+Math.round(retval.osd_differs / prev_int_pgs.length / 3 * 10000)/100+" %"
);
console.log(
"Total space: "+Math.round(retval.space*3*100)/100+" TB, space efficiency: "+
Math.round(retval.space*3/retval.total_space*10000)/100+" %"
);
}
function align_pgs(prev_int_pgs, int_pgs)
{
const aligned_pgs = [];
put_aligned_pgs(aligned_pgs, int_pgs, prev_int_pgs, (pg) => [ pg.join(':') ]);
put_aligned_pgs(aligned_pgs, int_pgs, prev_int_pgs, (pg) => [ pg[0]+'::'+pg[2], ':'+pg[1]+':'+pg[2], pg[0]+':'+pg[1]+':' ]);
put_aligned_pgs(aligned_pgs, int_pgs, prev_int_pgs, (pg) => [ pg[0]+'::', ':'+pg[1]+':', '::'+pg[2] ]);
const free_slots = prev_int_pgs.map((pg, i) => !aligned_pgs[i] ? i : null).filter(i => i != null);
for (const pg of int_pgs)
{
if (!free_slots.length)
{
throw new Error("Can't place unaligned PG");
}
aligned_pgs[free_slots.shift()] = pg;
}
return aligned_pgs;
}
function put_aligned_pgs(aligned_pgs, int_pgs, prev_int_pgs, keygen)
{
let prev_indexes = {};
for (let i = 0; i < prev_int_pgs.length; i++)
{
for (let k of keygen(prev_int_pgs[i]))
{
prev_indexes[k] = prev_indexes[k] || [];
prev_indexes[k].push(i);
}
}
PG: for (let i = int_pgs.length-1; i >= 0; i--)
{
let pg = int_pgs[i];
let keys = keygen(int_pgs[i]);
for (let k of keys)
{
while (prev_indexes[k] && prev_indexes[k].length)
{
let idx = prev_indexes[k].shift();
if (!aligned_pgs[idx])
{
aligned_pgs[idx] = pg;
int_pgs.splice(i, 1);
continue PG;
}
}
}
}
}
function all_combinations(osd_tree, count, ordered)
{
const hosts = Object.keys(osd_tree).sort();
const osds = Object.keys(osd_tree).reduce((a, c) => { a[c] = Object.keys(osd_tree[c]).sort(); return a; }, {});
let h = [ 0, 1, 2 ];
let o = [ 0, 0, 0 ];
const r = [];
while (!count || count < 0 || r.length < count)
{
let inc;
if (h[2] != h[1] && h[2] != h[0] && h[1] != h[0])
{
r.push(h.map((host_idx, i) => osds[hosts[host_idx]][o[i]]));
inc = 2;
while (inc >= 0)
{
o[inc]++;
if (o[inc] >= osds[hosts[h[inc]]].length)
{
o[inc] = 0;
inc--;
}
else
{
break;
}
}
}
else
{
inc = -1;
}
if (inc < 0)
{
// no osds left in current host combination, select the next one
o = [ 0, 0, 0 ];
h[2]++;
if (h[2] >= hosts.length)
{
h[1]++;
h[2] = ordered ? h[1]+1 : 0;
if ((ordered ? h[2] : h[1]) >= hosts.length)
{
h[0]++;
h[1] = ordered ? h[0]+1 : 0;
h[2] = ordered ? h[1]+1 : 0;
if ((ordered ? h[2] : h[0]) >= hosts.length)
{
break;
}
}
}
}
}
return r;
}
function pg_weights_space_efficiency(weights, pg_count, osd_tree)
{
const per_osd = {};
for (const pg_name in weights)
{
for (const osd of pg_name.substr(3).split(/_/))
{
per_osd[osd] = (per_osd[osd]||0) + weights[pg_name];
}
}
return pg_per_osd_space_efficiency(per_osd, pg_count, osd_tree);
}
function pg_list_space_efficiency(pgs, osd_tree)
{
const per_osd = {};
for (const pg of pgs)
{
for (const osd of pg)
{
per_osd[osd] = (per_osd[osd]||0) + 1;
}
}
return pg_per_osd_space_efficiency(per_osd, pgs.length, osd_tree);
}
function pg_per_osd_space_efficiency(per_osd, pg_count, osd_tree)
{
const all_weights = Object.assign.apply({}, Object.values(osd_tree));
// each PG gets randomly selected in 1/N cases
// => there are x PGs per OSD
// => an OSD is selected in x/N cases
// => total space * x/N <= OSD weight
// => total space <= OSD weight * N/x
let space;
for (let osd in per_osd)
{
const space_estimate = all_weights[osd] * pg_count / per_osd[osd];
if (space == null || space > space_estimate)
{
space = space_estimate;
}
}
return space;
}
module.exports = {
optimize_initial,
optimize_change,
print_change_stats,
pg_weights_space_efficiency,
pg_list_space_efficiency,
pg_per_osd_space_efficiency,
lp_solve,
make_single,
make_int_pgs,
get_int_pg_weights,
align_pgs,
all_combinations,
};