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datafusion-python/examples/sql-using-python-udf.py at main · nirnayroy/datafusion-python · GitHub
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sql-using-python-udf.py
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sql-using-python-udf.py
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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import
pyarrow
as
pa
from
datafusion
import
SessionContext
,
udf
# Define a user-defined function (UDF)
def
is_null
(
array
:
pa
.
Array
)
->
pa
.
Array
:
return
array
.
is_null
()
is_null_arr
=
udf
(
is_null
,
[
pa
.
int64
()],
pa
.
bool_
(),
"stable"
,
# This will be the name of the UDF in SQL
# If not specified it will by default the same as Python function name
name
=
"is_null"
,
)
# Create a context
ctx
=
SessionContext
()
# Create a datafusion DataFrame from a Python dictionary
ctx
.
from_pydict
({
"a"
: [
1
,
2
,
3
],
"b"
: [
4
,
None
,
6
]},
name
=
"t"
)
# Dataframe:
# +---+---+
# | a | b |
# +---+---+
# | 1 | 4 |
# | 2 | |
# | 3 | 6 |
# +---+---+
# Register UDF for use in SQL
ctx
.
register_udf
(
is_null_arr
)
# Query the DataFrame using SQL
result_df
=
ctx
.
sql
(
"select a, is_null(b) as b_is_null from t"
)
# Dataframe:
# +---+-----------+
# | a | b_is_null |
# +---+-----------+
# | 1 | false |
# | 2 | true |
# | 3 | false |
# +---+-----------+
assert
result_df
.
to_pydict
()[
"b_is_null"
]
==
[
False
,
True
,
False
]
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