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Vendor Update Go Libs (#13444)

* denisenkom/go-mssqldb untagged -> v0.9.0

* github.com/editorconfig/editorconfig-core-go v2.3.7 -> v2.3.8

* github.com/go-testfixtures/testfixtures v3.4.0 -> v3.4.1

* github.com/mholt/archiver v3.3.2 -> v3.5.0

* github.com/olivere/elastic v7.0.20 -> v7.0.21

* github.com/urfave/cli v1.22.4 -> v1.22.5

* github.com/xanzy/go-gitlab v0.38.1 -> v0.39.0

* github.com/yuin/goldmark-meta untagged -> v1.0.0

* github.com/ethantkoenig/rupture 0a76f03a811a -> c3b3b810dc77

* github.com/jaytaylor/html2text 8fb95d837f7d -> 3577fbdbcff7

* github.com/kballard/go-shellquote cd60e84ee657 -> 95032a82bc51

* github.com/msteinert/pam 02ccfbfaf0cc -> 913b8f8cdf8b

* github.com/unknwon/paginater 7748a72e0141 -> 042474bd0eae

* CI.restart()

Co-authored-by: techknowlogick <techknowlogick@gitea.io>
This commit is contained in:
6543 2020-11-06 19:41:42 +01:00 committed by GitHub
parent eebaa81f43
commit 30ce3731a1
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
184 changed files with 12387 additions and 2975 deletions

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@ -8,7 +8,6 @@ install:
notifications:
email: false
go:
- "1.12.x"
- "1.13.x"
- "1.14.x"
- tip

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@ -13,4 +13,6 @@ Forud Ghafouri (@fzerorubigd),
Joe Nall (@joenall),
(@fredim),
Edd Robinson (@e-dard),
Alexander Petrov (@alldroll)
Alexander Petrov (@alldroll),
Guy Molinari (@guymolinari),
Ling Jin (@JinLingChristopher)

View file

@ -3,7 +3,6 @@ roaring [![Build Status](https://travis-ci.org/RoaringBitmap/roaring.png)](https
![Go-CI](https://github.com/RoaringBitmap/roaring/workflows/Go-CI/badge.svg)
![Go-ARM-CI](https://github.com/RoaringBitmap/roaring/workflows/Go-ARM-CI/badge.svg)
![Go-Windows-CI](https://github.com/RoaringBitmap/roaring/workflows/Go-Windows-CI/badge.svg)
![Go-macos-CI](https://github.com/RoaringBitmap/roaring/workflows/Go-macos-CI/badge.svg)
=============
This is a go version of the Roaring bitmap data structure.
@ -56,6 +55,93 @@ This code is licensed under Apache License, Version 2.0 (ASL2.0).
Copyright 2016-... by the authors.
When should you use a bitmap?
===================================
Sets are a fundamental abstraction in
software. They can be implemented in various
ways, as hash sets, as trees, and so forth.
In databases and search engines, sets are often an integral
part of indexes. For example, we may need to maintain a set
of all documents or rows (represented by numerical identifier)
that satisfy some property. Besides adding or removing
elements from the set, we need fast functions
to compute the intersection, the union, the difference between sets, and so on.
To implement a set
of integers, a particularly appealing strategy is the
bitmap (also called bitset or bit vector). Using n bits,
we can represent any set made of the integers from the range
[0,n): the ith bit is set to one if integer i is present in the set.
Commodity processors use words of W=32 or W=64 bits. By combining many such words, we can
support large values of n. Intersections, unions and differences can then be implemented
as bitwise AND, OR and ANDNOT operations.
More complicated set functions can also be implemented as bitwise operations.
When the bitset approach is applicable, it can be orders of
magnitude faster than other possible implementation of a set (e.g., as a hash set)
while using several times less memory.
However, a bitset, even a compressed one is not always applicable. For example, if the
you have 1000 random-looking integers, then a simple array might be the best representation.
We refer to this case as the "sparse" scenario.
When should you use compressed bitmaps?
===================================
An uncompressed BitSet can use a lot of memory. For example, if you take a BitSet
and set the bit at position 1,000,000 to true and you have just over 100kB. That is over 100kB
to store the position of one bit. This is wasteful even if you do not care about memory:
suppose that you need to compute the intersection between this BitSet and another one
that has a bit at position 1,000,001 to true, then you need to go through all these zeroes,
whether you like it or not. That can become very wasteful.
This being said, there are definitively cases where attempting to use compressed bitmaps is wasteful.
For example, if you have a small universe size. E.g., your bitmaps represent sets of integers
from [0,n) where n is small (e.g., n=64 or n=128). If you are able to uncompressed BitSet and
it does not blow up your memory usage, then compressed bitmaps are probably not useful
to you. In fact, if you do not need compression, then a BitSet offers remarkable speed.
The sparse scenario is another use case where compressed bitmaps should not be used.
Keep in mind that random-looking data is usually not compressible. E.g., if you have a small set of
32-bit random integers, it is not mathematically possible to use far less than 32 bits per integer,
and attempts at compression can be counterproductive.
How does Roaring compares with the alternatives?
==================================================
Most alternatives to Roaring are part of a larger family of compressed bitmaps that are run-length-encoded
bitmaps. They identify long runs of 1s or 0s and they represent them with a marker word.
If you have a local mix of 1s and 0, you use an uncompressed word.
There are many formats in this family:
* Oracle's BBC is an obsolete format at this point: though it may provide good compression,
it is likely much slower than more recent alternatives due to excessive branching.
* WAH is a patented variation on BBC that provides better performance.
* Concise is a variation on the patented WAH. It some specific instances, it can compress
much better than WAH (up to 2x better), but it is generally slower.
* EWAH is both free of patent, and it is faster than all the above. On the downside, it
does not compress quite as well. It is faster because it allows some form of "skipping"
over uncompressed words. So though none of these formats are great at random access, EWAH
is better than the alternatives.
There is a big problem with these formats however that can hurt you badly in some cases: there is no random access. If you want to check whether a given value is present in the set, you have to start from the beginning and "uncompress" the whole thing. This means that if you want to intersect a big set with a large set, you still have to uncompress the whole big set in the worst case...
Roaring solves this problem. It works in the following manner. It divides the data into chunks of 2<sup>16</sup> integers
(e.g., [0, 2<sup>16</sup>), [2<sup>16</sup>, 2 x 2<sup>16</sup>), ...). Within a chunk, it can use an uncompressed bitmap, a simple list of integers,
or a list of runs. Whatever format it uses, they all allow you to check for the present of any one value quickly
(e.g., with a binary search). The net result is that Roaring can compute many operations much faster than run-length-encoded
formats like WAH, EWAH, Concise... Maybe surprisingly, Roaring also generally offers better compression ratios.
### References

View file

@ -359,28 +359,17 @@ func (ac *arrayContainer) iorArray(value2 *arrayContainer) container {
len1 := value1.getCardinality()
len2 := value2.getCardinality()
maxPossibleCardinality := len1 + len2
if maxPossibleCardinality > arrayDefaultMaxSize { // it could be a bitmap!
bc := newBitmapContainer()
for k := 0; k < len(value2.content); k++ {
v := value2.content[k]
i := uint(v) >> 6
mask := uint64(1) << (v % 64)
bc.bitmap[i] |= mask
}
for k := 0; k < len(ac.content); k++ {
v := ac.content[k]
i := uint(v) >> 6
mask := uint64(1) << (v % 64)
bc.bitmap[i] |= mask
}
bc.cardinality = int(popcntSlice(bc.bitmap))
if bc.cardinality <= arrayDefaultMaxSize {
return bc.toArrayContainer()
}
return bc
}
if maxPossibleCardinality > cap(value1.content) {
newcontent := make([]uint16, 0, maxPossibleCardinality)
// doubling the capacity reduces new slice allocations in the case of
// repeated calls to iorArray().
newSize := 2 * maxPossibleCardinality
// the second check is to handle overly large array containers
// and should not occur in normal usage,
// as all array containers should be at most arrayDefaultMaxSize
if newSize > 2*arrayDefaultMaxSize && maxPossibleCardinality <= 2*arrayDefaultMaxSize {
newSize = 2 * arrayDefaultMaxSize
}
newcontent := make([]uint16, 0, newSize)
copy(newcontent[len2:maxPossibleCardinality], ac.content[0:len1])
ac.content = newcontent
} else {
@ -388,6 +377,13 @@ func (ac *arrayContainer) iorArray(value2 *arrayContainer) container {
}
nl := union2by2(value1.content[len2:maxPossibleCardinality], value2.content, ac.content)
ac.content = ac.content[:nl] // reslice to match actual used capacity
if nl > arrayDefaultMaxSize {
// Only converting to a bitmap when arrayDefaultMaxSize
// is actually exceeded minimizes conversions in the case of repeated
// calls to iorArray().
return ac.toBitmapContainer()
}
return ac
}

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@ -1,6 +1,6 @@
module github.com/RoaringBitmap/roaring
go 1.12
go 1.14
require (
github.com/glycerine/go-unsnap-stream v0.0.0-20181221182339-f9677308dec2
@ -13,4 +13,6 @@ require (
github.com/stretchr/testify v1.4.0
github.com/tinylib/msgp v1.1.0
github.com/willf/bitset v1.1.10
golang.org/x/lint v0.0.0-20200302205851-738671d3881b // indirect
golang.org/x/tools v0.0.0-20200928182047-19e03678916f // indirect
)

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@ -24,6 +24,31 @@ github.com/tinylib/msgp v1.1.0 h1:9fQd+ICuRIu/ue4vxJZu6/LzxN0HwMds2nq/0cFvxHU=
github.com/tinylib/msgp v1.1.0/go.mod h1:+d+yLhGm8mzTaHzB+wgMYrodPfmZrzkirds8fDWklFE=
github.com/willf/bitset v1.1.10 h1:NotGKqX0KwQ72NUzqrjZq5ipPNDQex9lo3WpaS8L2sc=
github.com/willf/bitset v1.1.10/go.mod h1:RjeCKbqT1RxIR/KWY6phxZiaY1IyutSBfGjNPySAYV4=
github.com/yuin/goldmark v1.2.1/go.mod h1:3hX8gzYuyVAZsxl0MRgGTJEmQBFcNTphYh9decYSb74=
golang.org/x/crypto v0.0.0-20190308221718-c2843e01d9a2/go.mod h1:djNgcEr1/C05ACkg1iLfiJU5Ep61QUkGW8qpdssI0+w=
golang.org/x/crypto v0.0.0-20191011191535-87dc89f01550/go.mod h1:yigFU9vqHzYiE8UmvKecakEJjdnWj3jj499lnFckfCI=
golang.org/x/crypto v0.0.0-20200622213623-75b288015ac9/go.mod h1:LzIPMQfyMNhhGPhUkYOs5KpL4U8rLKemX1yGLhDgUto=
golang.org/x/lint v0.0.0-20200302205851-738671d3881b h1:Wh+f8QHJXR411sJR8/vRBTZ7YapZaRvUcLFFJhusH0k=
golang.org/x/lint v0.0.0-20200302205851-738671d3881b/go.mod h1:3xt1FjdF8hUf6vQPIChWIBhFzV8gjjsPE/fR3IyQdNY=
golang.org/x/mod v0.1.1-0.20191105210325-c90efee705ee/go.mod h1:QqPTAvyqsEbceGzBzNggFXnrqF1CaUcvgkdR5Ot7KZg=
golang.org/x/mod v0.3.0/go.mod h1:s0Qsj1ACt9ePp/hMypM3fl4fZqREWJwdYDEqhRiZZUA=
golang.org/x/net v0.0.0-20190404232315-eb5bcb51f2a3/go.mod h1:t9HGtf8HONx5eT2rtn7q6eTqICYqUVnKs3thJo3Qplg=
golang.org/x/net v0.0.0-20190620200207-3b0461eec859/go.mod h1:z5CRVTTTmAJ677TzLLGU+0bjPO0LkuOLi4/5GtJWs/s=
golang.org/x/net v0.0.0-20200822124328-c89045814202/go.mod h1:/O7V0waA8r7cgGh81Ro3o1hOxt32SMVPicZroKQ2sZA=
golang.org/x/sync v0.0.0-20190423024810-112230192c58/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20200625203802-6e8e738ad208/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sys v0.0.0-20190215142949-d0b11bdaac8a/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20190412213103-97732733099d/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20200323222414-85ca7c5b95cd/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/text v0.3.0/go.mod h1:NqM8EUOU14njkJ3fqMW+pc6Ldnwhi/IjpwHt7yyuwOQ=
golang.org/x/tools v0.0.0-20191119224855-298f0cb1881e/go.mod h1:b+2E5dAYhXwXZwtnZ6UAqBI28+e2cm9otk0dWdXHAEo=
golang.org/x/tools v0.0.0-20200130002326-2f3ba24bd6e7 h1:EBZoQjiKKPaLbPrbpssUfuHtwM6KV/vb4U85g/cigFY=
golang.org/x/tools v0.0.0-20200130002326-2f3ba24bd6e7/go.mod h1:TB2adYChydJhpapKDTa4BR/hXlZSLoq2Wpct/0txZ28=
golang.org/x/tools v0.0.0-20200928182047-19e03678916f h1:VwGa2Wf+rHGIxvsssCkUNIyFv8jQY0VCBCNWtikoWq0=
golang.org/x/tools v0.0.0-20200928182047-19e03678916f/go.mod h1:z6u4i615ZeAfBE4XtMziQW1fSVJXACjjbWkB/mvPzlU=
golang.org/x/xerrors v0.0.0-20190717185122-a985d3407aa7/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20191011141410-1b5146add898/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20200804184101-5ec99f83aff1/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405 h1:yhCVgyC4o1eVCa2tZl7eS0r+SDo693bJlVdllGtEeKM=
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/yaml.v2 v2.2.2 h1:ZCJp+EgiOT7lHqUV2J862kp8Qj64Jo6az82+3Td9dZw=

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@ -345,9 +345,9 @@ func newIntReverseIterator(a *Bitmap) *intReverseIterator {
// ManyIntIterable allows you to iterate over the values in a Bitmap
type ManyIntIterable interface {
// pass in a buffer to fill up with values, returns how many values were returned
// NextMany fills buf up with values, returns how many values were returned
NextMany(buf []uint32) int
// pass in a buffer to fill up with 64 bit values, returns how many values were returned
// NextMany64 fills up buf with 64 bit values, uses hs as a mask (OR), returns how many values were returned
NextMany64(hs uint64, buf []uint64) int
}
@ -1006,7 +1006,7 @@ main:
}
s2 = x2.highlowcontainer.getKeyAtIndex(pos2)
} else {
rb.highlowcontainer.replaceKeyAndContainerAtIndex(pos1, s1, rb.highlowcontainer.getWritableContainerAtIndex(pos1).ior(x2.highlowcontainer.getContainerAtIndex(pos2)), false)
rb.highlowcontainer.replaceKeyAndContainerAtIndex(pos1, s1, rb.highlowcontainer.getUnionedWritableContainer(pos1, x2.highlowcontainer.getContainerAtIndex(pos2)), false)
pos1++
pos2++
if (pos1 == length1) || (pos2 == length2) {
@ -1581,7 +1581,3 @@ func (rb *Bitmap) Stats() Statistics {
}
return stats
}
func (rb *Bitmap) FillLeastSignificant32bits(x []uint64, i uint64, mask uint64) {
rb.ManyIterator().NextMany64(mask, x[i:])
}

View file

@ -328,6 +328,17 @@ func (ra *roaringArray) getFastContainerAtIndex(i int, needsWriteable bool) cont
return c
}
// getUnionedWritableContainer switches behavior for in-place Or
// depending on whether the container requires a copy on write.
// If it does using the non-inplace or() method leads to fewer allocations.
func (ra *roaringArray) getUnionedWritableContainer(pos int, other container) container {
if ra.needCopyOnWrite[pos] {
return ra.getContainerAtIndex(pos).or(other)
}
return ra.getContainerAtIndex(pos).ior(other)
}
func (ra *roaringArray) getWritableContainerAtIndex(i int) container {
if ra.needCopyOnWrite[i] {
ra.containers[i] = ra.containers[i].clone()

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@ -1,4 +1,4 @@
// +build !amd64,!386 appengine
// +build !amd64,!386,!arm,!arm64,!ppc64le,!mipsle,!mips64le,!mips64p32le,!wasm appengine
package roaring

View file

@ -1,4 +1,4 @@
// +build 386 amd64,!appengine
// +build 386,!appengine amd64,!appengine arm,!appengine arm64,!appengine ppc64le,!appengine mipsle,!appengine mips64le,!appengine mips64p32le,!appengine wasm,!appengine
package roaring

View file

@ -135,66 +135,6 @@ func exclusiveUnion2by2(set1 []uint16, set2 []uint16, buffer []uint16) int {
return pos
}
func union2by2(set1 []uint16, set2 []uint16, buffer []uint16) int {
pos := 0
k1 := 0
k2 := 0
if 0 == len(set2) {
buffer = buffer[:len(set1)]
copy(buffer, set1[:])
return len(set1)
}
if 0 == len(set1) {
buffer = buffer[:len(set2)]
copy(buffer, set2[:])
return len(set2)
}
s1 := set1[k1]
s2 := set2[k2]
buffer = buffer[:cap(buffer)]
for {
if s1 < s2 {
buffer[pos] = s1
pos++
k1++
if k1 >= len(set1) {
copy(buffer[pos:], set2[k2:])
pos += len(set2) - k2
break
}
s1 = set1[k1]
} else if s1 == s2 {
buffer[pos] = s1
pos++
k1++
k2++
if k1 >= len(set1) {
copy(buffer[pos:], set2[k2:])
pos += len(set2) - k2
break
}
if k2 >= len(set2) {
copy(buffer[pos:], set1[k1:])
pos += len(set1) - k1
break
}
s1 = set1[k1]
s2 = set2[k2]
} else { // if (set1[k1]>set2[k2])
buffer[pos] = s2
pos++
k2++
if k2 >= len(set2) {
copy(buffer[pos:], set1[k1:])
pos += len(set1) - k1
break
}
s2 = set2[k2]
}
}
return pos
}
func union2by2Cardinality(set1 []uint16, set2 []uint16) int {
pos := 0
k1 := 0

View file

@ -0,0 +1,6 @@
// +build arm64,!gccgo,!appengine
package roaring
//go:noescape
func union2by2(set1 []uint16, set2 []uint16, buffer []uint16) (size int)

132
vendor/github.com/RoaringBitmap/roaring/setutil_arm64.s generated vendored Normal file
View file

@ -0,0 +1,132 @@
// +build arm64,!gccgo,!appengine
#include "textflag.h"
// This implements union2by2 using golang's version of arm64 assembly
// The algorithm is very similar to the generic one,
// but makes better use of arm64 features so is notably faster.
// The basic algorithm structure is as follows:
// 1. If either set is empty, copy the other set into the buffer and return the length
// 2. Otherwise, load the first element of each set into a variable (s1 and s2).
// 3. a. Compare the values of s1 and s2.
// b. add the smaller one to the buffer.
// c. perform a bounds check before incrementing.
// If one set is finished, copy the rest of the other set over.
// d. update s1 and or s2 to the next value, continue loop.
//
// Past the fact of the algorithm, this code makes use of several arm64 features
// Condition Codes:
// arm64's CMP operation sets 4 bits that can be used for branching,
// rather than just true or false.
// As a consequence, a single comparison gives enough information to distinguish the three cases
//
// Post-increment pointers after load/store:
// Instructions like `MOVHU.P 2(R0), R6`
// increment the register by a specified amount, in this example 2.
// Because uint16's are exactly 2 bytes and the length of the slices
// is part of the slice header,
// there is no need to separately track the index into the slice.
// Instead, the code can calculate the final read value and compare against that,
// using the post-increment reads to move the pointers along.
//
// TODO: CALL out to memmove once the list is exhausted.
// Right now it moves the necessary shorts so that the remaining count
// is a multiple of 4 and then copies 64 bits at a time.
TEXT ·union2by2(SB), NOSPLIT, $0-80
// R0, R1, and R2 for the pointers to the three slices
MOVD set1+0(FP), R0
MOVD set2+24(FP), R1
MOVD buffer+48(FP), R2
//R3 and R4 will be the values at which we will have finished reading set1 and set2.
// R3 should be R0 + 2 * set1_len+8(FP)
MOVD set1_len+8(FP), R3
MOVD set2_len+32(FP), R4
ADD R3<<1, R0, R3
ADD R4<<1, R1, R4
//Rather than counting the number of elements added separately
//Save the starting register of buffer.
MOVD buffer+48(FP), R5
// set1 is empty, just flush set2
CMP R0, R3
BEQ flush_right
// set2 is empty, just flush set1
CMP R1, R4
BEQ flush_left
// R6, R7 are the working space for s1 and s2
MOVD ZR, R6
MOVD ZR, R7
MOVHU.P 2(R0), R6
MOVHU.P 2(R1), R7
loop:
CMP R6, R7
BEQ pop_both // R6 == R7
BLS pop_right // R6 > R7
//pop_left: // R6 < R7
MOVHU.P R6, 2(R2)
CMP R0, R3
BEQ pop_then_flush_right
MOVHU.P 2(R0), R6
JMP loop
pop_both:
MOVHU.P R6, 2(R2) //could also use R7, since they are equal
CMP R0, R3
BEQ flush_right
CMP R1, R4
BEQ flush_left
MOVHU.P 2(R0), R6
MOVHU.P 2(R1), R7
JMP loop
pop_right:
MOVHU.P R7, 2(R2)
CMP R1, R4
BEQ pop_then_flush_left
MOVHU.P 2(R1), R7
JMP loop
pop_then_flush_right:
MOVHU.P R7, 2(R2)
flush_right:
MOVD R1, R0
MOVD R4, R3
JMP flush_left
pop_then_flush_left:
MOVHU.P R6, 2(R2)
flush_left:
CMP R0, R3
BEQ return
//figure out how many bytes to slough off. Must be a multiple of two
SUB R0, R3, R4
ANDS $6, R4
BEQ long_flush //handles the 0 mod 8 case
SUBS $4, R4, R4 // since possible values are 2, 4, 6, this splits evenly
BLT pop_single // exactly the 2 case
MOVW.P 4(R0), R6
MOVW.P R6, 4(R2)
BEQ long_flush // we're now aligned by 64 bits, as R4==4, otherwise 2 more
pop_single:
MOVHU.P 2(R0), R6
MOVHU.P R6, 2(R2)
long_flush:
// at this point we know R3 - R0 is a multiple of 8.
CMP R0, R3
BEQ return
MOVD.P 8(R0), R6
MOVD.P R6, 8(R2)
JMP long_flush
return:
// number of shorts written is (R5 - R2) >> 1
SUB R5, R2
LSR $1, R2, R2
MOVD R2, size+72(FP)
RET

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@ -0,0 +1,63 @@
// +build !arm64 gccgo appengine
package roaring
func union2by2(set1 []uint16, set2 []uint16, buffer []uint16) int {
pos := 0
k1 := 0
k2 := 0
if 0 == len(set2) {
buffer = buffer[:len(set1)]
copy(buffer, set1[:])
return len(set1)
}
if 0 == len(set1) {
buffer = buffer[:len(set2)]
copy(buffer, set2[:])
return len(set2)
}
s1 := set1[k1]
s2 := set2[k2]
buffer = buffer[:cap(buffer)]
for {
if s1 < s2 {
buffer[pos] = s1
pos++
k1++
if k1 >= len(set1) {
copy(buffer[pos:], set2[k2:])
pos += len(set2) - k2
break
}
s1 = set1[k1]
} else if s1 == s2 {
buffer[pos] = s1
pos++
k1++
k2++
if k1 >= len(set1) {
copy(buffer[pos:], set2[k2:])
pos += len(set2) - k2
break
}
if k2 >= len(set2) {
copy(buffer[pos:], set1[k1:])
pos += len(set1) - k1
break
}
s1 = set1[k1]
s2 = set2[k2]
} else { // if (set1[k1]>set2[k2])
buffer[pos] = s2
pos++
k2++
if k2 >= len(set2) {
copy(buffer[pos:], set1[k1:])
pos += len(set1) - k1
break
}
s2 = set2[k2]
}
}
return pos
}