Use cases

Write a Python UDF script and save it as a sum_pandas.py file. The following code provides an example:

from odps.udf import annotate
import pandas as pd

@annotate("string, string -> string")
class SumColumns(object):
    def evaluate(self, arg1, arg2):
        # Convert the input arguments to a pandas DataFrame.
        df = pd.DataFrame({'col1': arg1.split(','), 'col2': arg2.split(',')})

        # Process the data by using pandas.
        # This example calculates the sum of two columns.
        df['sum'] = df['col1'].astype(int) + df['col2'].astype(int)

        # Convert the result to a string and return it.
        result = ','.join(df['sum'].astype(str).values)
        return result

Upload the sum_pandas.py script as a resource to your MaxCompute project. For more information, see Add resources. The following sample command shows how to upload the script:

ADD PY sum_pandas.py -f;

Register the sum_pandas.py script that you uploaded as the SumColumns user-defined function. For more information, see Register a function. The following sample command shows how to register the function:

CREATE FUNCTION SumColumns AS 'sum_pandas.SumColumns' USING 'sum_pandas.py';

Create a test table named testsum and insert test data into the table.

CREATE TABLE testsum (col1 string, col2 string);
INSERT INTO testsum VALUES ('1,2,3','1,2,3'),('1,2,3','3,2,1'),('1,2,3','4,5,6');

Call the UDF and specify an existing image by using a flag.

set odps.sql.python.version=cp37;
set odps.session.image = <image_name>;
SELECT SumColumns(col1,col2) AS result FROM testsum;

The following result is returned:

+------------+
| result     |
+------------+
| 2,4,6      |
| 4,4,4      |
| 5,7,9      |
+------------+

Create a test table named test_float_col and insert test data into the table.

CREATE TABLE test_float_col (col1 double);
INSERT INTO test_float_col VALUES (3.75),(2.51);

Write a PyODPS script to calculate the value of psi(col1), save the script as a psi_col.py file, and then run the file. The following code provides an example:

import os
from odps import ODPS, options

def my_psi(v):
    from scipy.special import psi

    return float(psi(v))

# If the project has isolation enabled, the following option is not required.
options.sql.settings = {"odps.isolation.session.enable": True}

o = ODPS(
      # Make sure that the ALIBABA_CLOUD_ACCESS_KEY_ID environment variable is set to your AccessKey ID,
      # and the ALIBABA_CLOUD_ACCESS_KEY_SECRET environment variable is set to your AccessKey secret.
      # We recommend that you do not hardcode your AccessKey ID and AccessKey secret in the code.
      os.getenv('ALIBABA_CLOUD_ACCESS_KEY_ID'),
      os.getenv('ALIBABA_CLOUD_ACCESS_KEY_SECRET'),
      project='your-default-project',
      endpoint='your-end-point'
)

df = o.get_table("test_float_col").to_df()
# Execute the job and retrieve the result.
df.col1.map(my_psi).execute(image='scipy')
# Save the result to another table.
df.col1.map(my_psi).persist("result_table", image='scipy')

View the results in the result_table table.

SELECT * FROM result_table

The following result is returned:

+------------+
| col1       |
+------------+
| 1.1825373886117962 |
| 0.7080484451910534 |
+------------+

Create a test table named test_float_col and insert test data into the table.

CREATE TABLE test_float_col (col1 double);
INSERT INTO test_float_col VALUES (3.75),(2.51);

Write a MaxFrame script to calculate the value of psi(col1), save the script as a psi_col.py file, and then run the file. The following code provides an example:

import os
from odps import ODPS, options
from maxframe.session import new_session
import maxframe.dataframe as md


from maxframe.config import options
from maxframe import config

# Reference the built-in SciPy image.
config.options.sql.settings = {
    "odps.session.image": "scipy"
}
def my_psi(v):
    from scipy.special import psi
    return float(psi(v))

o = ODPS(
      # Make sure that the ALIBABA_CLOUD_ACCESS_KEY_ID environment variable is set to your AccessKey ID,
      # and the ALIBABA_CLOUD_ACCESS_KEY_SECRET environment variable is set to your AccessKey secret.
      # We recommend that you do not hardcode your AccessKey ID and AccessKey secret in the code.
      os.getenv('ALIBABA_CLOUD_ACCESS_KEY_ID'),
      os.getenv('ALIBABA_CLOUD_ACCESS_KEY_SECRET'),
      project='your-default-project',
      endpoint='your-end-point'
)

# Create a MaxFrame session.
session = new_session(o)
df = md.read_odps_table('test_float_col')

# Execute the job and retrieve the result.
print(df.col1.map(my_psi).execute().fetch())

The following result is returned:

0    1.182537
1    0.708048
Name: col1, dtype: float64