Implementation Status

The following tables summarize the features available in the various official GraphAr libraries. All libraries currently follow version 1.0.0 of the GraphAr format.

Data Types

Data type (primitive)	C++	Java	Scala	Python
Boolean	✓	✓	✓	✓
Int32	✓	✓	✓	✓
Int64	✓	✓	✓	✓
Float	✓	✓	✓	✓
Double	✓	✓	✓	✓
String	✓	✓	✓	✓
Date	✓
Timestamp	✓
Time

Data type (nested)	C++	Java	Scala	Python
List (*)	✓

note

• (*) The data type of List is not supported by the CSV payload file format.

Payload Data File Formats

Format	C++	Java	Scala	Python
CSV	R/W	R (1)	R/W	R/W (2)
ORC	R/W	R (1)	R/W	R/W (2)
Parquet	R/W	R (1)	R/W	R/W (2)
Avro
HDF5
JSON

note

• R - Read supported
• W - Write supported

Supported compression methods for the file formats:

Compression	C++	Java	Scala	Python
ZSTD (*)	✓	✓	✓	✓

note

• (*) Compression is not supported by the CSV payload file format.

Property

Property feature	C++	Java	Scala	Python
primary key	✓	✓	✓	✓
nullable	✓		✓	✓

Supported operations in Property:

Property operation	C++	Java	Scala	Python
create	✓	✓ (1)	✓	✓ (2)
get_name	✓	✓ (1)	✓	✓ (2)
is_primary_key	✓	✓ (1)	✓	✓ (2)
is_nullable	✓		✓	✓ (2)

Property Group

Property Group (operation)	C++	Java (1)	Scala	Python (2)
create	✓	✓	✓	✓
add property	✓	✓	✓	✓
remove property
get properties	✓	✓	✓	✓
check property	✓	✓
get file type	✓	✓	✓	✓
get path prefix	✓	✓	✓	✓
check validation	✓

Adjacency List

Adjacency List (type)	C++	Java	Scala	Python
CSR	✓	✓	✓	✓
CSC	✓	✓	✓	✓
COO	✓	✓	✓	✓

Supported operations in Adjacency List:

Adjacency List (operation)	C++	Java (1)	Scala	Python (2)
create	✓		✓	✓
get adjacency type	✓		✓	✓
get file type	✓		✓	✓
get path prefix	✓		✓	✓
check validation	✓

Vertex

Vertex features:

Vertex feature	C++	Java	Scala	Python
label	✓	✓	✓	✓
tag
chunk based	✓	✓	✓	✓
property group	✓	✓	✓	✓

note

• label is the vertex label, which is a unique identifier for the vertex.
• tag is the vertex tag, which is tag or category for the vertex.

Supported operations in Vertex Info:

Vertex Info (operation)	C++	Java (1)	Scala	Python (2)
create	✓	✓	✓	✓
add group	✓	✓	✓	✓
remove group
get label	✓	✓	✓	✓
get chunk size	✓	✓	✓	✓
get groups	✓	✓	✓	✓
get path prefix	✓	✓	✓	✓
check property	✓	✓	✓	✓
check validation	✓		✓	✓
serialize	✓	✓	✓	✓
deserialize	✓	✓	✓	✓

Edge

Edge features:

Edge feature	C++	Java	Scala	Python
label	✓	✓	✓	✓
chunk based	✓	✓	✓	✓
property group	✓	✓	✓	✓
adjacent list	✓	✓	✓	✓
directed	✓	✓	✓	✓

Supported operations in Edge Info:

Edge Info (operation)	C++	Java (1)	Scala	Python (2)
create	✓	✓	✓	✓
add group	✓	✓	✓	✓
remove group
add adj list	✓	✓	✓	✓
remove adj list
get label	✓	✓	✓	✓
get source label	✓	✓	✓	✓
get dest label	✓	✓	✓	✓
get chunk size	✓	✓	✓	✓
get source chunk size	✓	✓	✓	✓
get dest chunk size	✓	✓	✓	✓
get groups	✓	✓	✓	✓
check adj list	✓	✓	✓	✓
check property	✓	✓	✓	✓
get file type	✓	✓	✓	✓
get path prefix	✓	✓	✓	✓
is directed	✓	✓	✓	✓
check validation	✓		✓	✓
serialize	✓	✓	✓	✓
deserialize	✓	✓	✓	✓

note

• <source label, label, dest label> is the unique identifier for the edge type.

Graph

Graph	C++	Java	Scala	Python
labeled vertex (with property)	✓	✓	✓	✓
labeled edge (with property)	✓	✓	✓	✓
extra info	✓

Supported operations in Graph Info:

Graph Info (operation)	C++	Java (1)	Scala	Python (2)
create	✓	✓	✓	✓
add vertex	✓	✓	✓	✓
remove vertex
add edge	✓	✓	✓	✓
remove edge
get name	✓	✓	✓	✓
get vertex	✓	✓	✓	✓
get edge	✓	✓	✓	✓
add extra info
remove extra info
get extra info	✓
check validation	✓
serialize	✓	✓	✓	✓
deserialize	✓	✓	✓	✓

note

• (1) Through fastFFI bindings to the GraphAr C++ library.

• (2) Through py4j bindings to the GraphAr Spark library.

Libraries Version Compatibility

GraphAr C++ Version	C++	CMake	Format Version
0.11.x	17+	2.8+	1.0.0

GraphAr Java Version	Java	Maven	Format Version
0.1.0	1.8	3.6+	1.0.0

GraphAr Spark Version	Apache Spark Version	Scala Version	Java Version	Hadoop Version	Format Version
0.1.0	3.2.x-3.3.x	2.12.x	1.8, 11	3	1.0.0

GraphAr PySpark Version	Python Version	PySpark Version	Hadoop Version	Format Version
0.1.0	3.8+	3.2.x	3	1.0.0

note

• Since the GraphAr PySpark library is bindings to the GraphAr Spark library, the PySpark version should be compatible with the Spark version.