Apache Arrow is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. It also provides computational libraries and zero-copy streaming messaging and inter-process communication.
arrow makes use of reference counting so that it can track when memory buffers are no longer used. This allows
arrow to update resource accounting, pool memory such and track overall memory usage as objects are created
and released. Types expose two methods to deal with this pattern. The Retain
method will increase the
reference count by 1 and Release
method will reduce the count by 1. Once the reference count of an object
is zero, any associated object will be freed. Retain
and Release
are safe to call from multiple goroutines.
-
If you are passed an object and wish to take ownership of it, you must call
Retain
. You must later pair this with a call toRelease
when you no longer need the object. "Taking ownership" typically means you wish to access the object outside the scope of the current function call. -
You own any object you create via functions whose name begins with
New
orCopy
or when receiving an object over a channel. Therefore you must callRelease
once you no longer need the object. -
If you send an object over a channel, you must call
Retain
before sending it as the receiver is assumed to own the object and will later callRelease
when it no longer needs the object.
The arrow package makes extensive use of c2goasm to leverage LLVM's advanced optimizer and generate PLAN9
assembly functions from C/C++ code. The arrow package can be compiled without these optimizations using the noasm
build tag. Alternatively, by configuring an environment variable, it is possible to dynamically configure which
architecture optimizations are used at runtime.
See the cpu
package README for a description of this environment variable.
The following benchmarks demonstrate summing an array of 8192 values using various optimizations.
Disable no architecture optimizations (thus using AVX2):
$ INTEL_DISABLE_EXT=NONE go test -bench=8192 -run=. ./math
goos: darwin
goarch: amd64
pkg: github.com/apache/arrow/go/arrow/math
BenchmarkFloat64Funcs_Sum_8192-8 2000000 687 ns/op 95375.41 MB/s
BenchmarkInt64Funcs_Sum_8192-8 2000000 719 ns/op 91061.06 MB/s
BenchmarkUint64Funcs_Sum_8192-8 2000000 691 ns/op 94797.29 MB/s
PASS
ok github.com/apache/arrow/go/arrow/math 6.444s
NOTE: NONE
is simply ignored, thus enabling optimizations for AVX2 and SSE4
Disable AVX2 architecture optimizations:
$ INTEL_DISABLE_EXT=AVX2 go test -bench=8192 -run=. ./math
goos: darwin
goarch: amd64
pkg: github.com/apache/arrow/go/arrow/math
BenchmarkFloat64Funcs_Sum_8192-8 1000000 1912 ns/op 34263.63 MB/s
BenchmarkInt64Funcs_Sum_8192-8 1000000 1392 ns/op 47065.57 MB/s
BenchmarkUint64Funcs_Sum_8192-8 1000000 1405 ns/op 46636.41 MB/s
PASS
ok github.com/apache/arrow/go/arrow/math 4.786s
Disable ALL architecture optimizations, thus using pure Go implementation:
$ INTEL_DISABLE_EXT=ALL go test -bench=8192 -run=. ./math
goos: darwin
goarch: amd64
pkg: github.com/apache/arrow/go/arrow/math
BenchmarkFloat64Funcs_Sum_8192-8 200000 10285 ns/op 6371.41 MB/s
BenchmarkInt64Funcs_Sum_8192-8 500000 3892 ns/op 16837.37 MB/s
BenchmarkUint64Funcs_Sum_8192-8 500000 3929 ns/op 16680.00 MB/s
PASS
ok github.com/apache/arrow/go/arrow/math 6.179s
The first milestone was to implement the necessary Array types in order to use them internally in the ifql execution engine and storage layers of InfluxDB.
- Allocations are 64-byte aligned and padded to 8-bytes
Primitive types
- Signed and unsigned 8, 16, 32 and 64 bit integers
- 32 and 64 bit floats
- Packed LSB booleans
- Variable-length binary
- String (valid UTF-8)
- Half-float (16-bit)
- Null (no physical storage)
Parametric types
- Timestamp
- Interval (year/month or day/time)
- Date32 (days since UNIX epoch)
- Date64 (milliseconds since UNIX epoch)
- Time32 (seconds or milliseconds since midnight)
- Time64 (microseconds or nanoseconds since midnight)
- Decimal (128-bit)
- Fixed-sized binary
- List
- Struct
- Union
- Dense
- Sparse
- Dictionary
- Dictionary encoding
- Data types (implemented arrays)
- Field
- Schema
Serialization is planned for a future iteration.
- Flat buffers for serializing metadata
- Record Batch
- Table