A user-defined function framework for Apache Arrow
Project description
Arrow UDF Python Server
Installation
pip install arrow-udf
Usage
Define functions in a Python file:
# udf.py
from arrow_udf import udf, udtf, UdfServer
import struct
import socket
# Define a scalar function
@udf(input_types=['INT', 'INT'], result_type='INT')
def gcd(x, y):
while y != 0:
(x, y) = (y, x % y)
return x
# Define a scalar function that returns multiple values (within a struct)
@udf(input_types=['BINARY'], result_type='STRUCT<src_addr: STRING, dst_addr: STRING, src_port: INT16, dst_port: INT16>')
def extract_tcp_info(tcp_packet: bytes):
src_addr, dst_addr = struct.unpack('!4s4s', tcp_packet[12:20])
src_port, dst_port = struct.unpack('!HH', tcp_packet[20:24])
src_addr = socket.inet_ntoa(src_addr)
dst_addr = socket.inet_ntoa(dst_addr)
return {
'src_addr': src_addr,
'dst_addr': dst_addr,
'src_port': src_port,
'dst_port': dst_port,
}
# Define a table function
@udtf(input_types='INT', result_types='INT')
def series(n):
for i in range(n):
yield i
# Start a UDF server
if __name__ == '__main__':
server = UdfServer(location="0.0.0.0:8815")
server.add_function(gcd)
server.add_function(extract_tcp_info)
server.add_function(series)
server.serve()
Start the UDF server:
python3 udf.py
Data Types
Arrow Type | Python Type |
---|---|
boolean |
bool |
int8 |
int |
int16 |
int |
int32 |
int |
int64 |
int |
uint8 |
int |
uint16 |
int |
uint32 |
int |
uint64 |
int |
float32 |
float |
float32 |
float |
date32 |
datetime.date |
time64 |
datetime.time |
timestamp |
datetime.datetime |
interval |
MonthDayNano / (int, int, int) (fields can be obtained by months() , days() and nanoseconds() from MonthDayNano ) |
string |
str |
binary |
bytes |
large_string |
str |
large_binary |
bytes |
Extension types:
Data type | Metadata | Python Type |
---|---|---|
decimal |
arrowudf.decimal |
decimal.Decimal |
json |
arrowudf.json |
any |
Project details
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