Details
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Bug
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Status: Closed
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Minor
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Resolution: Fixed
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None
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None
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None
Description
The issue is that PCA train does not run when the grouping column is text (have not tested other non-integer data types). See below for error reproduced on a modified example from the docs.
DROP TABLE IF EXISTS mat_group_text;
CREATE TABLE mat_group_text (
id integer,
row_vec double precision[],
matrix_id_text text
);
INSERT INTO mat_group_text VALUES
(1, '{1,2,3}', '1'),
(2, '{2,1,2}', '1'),
(3, '{3,2,1}', '1'),
(4, '{1,2,3,4,5}', '2'),
(5, '{2,5,2,4,1}', '2'),
(6, '{5,4,3,2,1}', '2');
DROP TABLE IF EXISTS result_table_group_text, result_table_group_text_mean;
SELECT madlib.pca_train('mat_group_text', – Source table
'result_table_group_text', – Output table
'id', – Row id of source table
0.8, – Proportion of variance
'matrix_id_text'); – Grouping column
SELECT * FROM result_table_group_text ORDER BY matrix_id_text, row_id_text;
– NOTICE: table "result_table_group_text" does not exist, skipping
– NOTICE: table "result_table_group_text_mean" does not exist, skipping
– ERROR: plpy.SPIError: plpy.SPIError: operator does not exist: text = integer
– LINE 5: WHERE matrix_id_text=1
– ^
– HINT: No operator matches the given name and argument type(s). You might need to add explicit type casts.
– QUERY:
– CREATE TABLE pg_temp._madlib_temp_57228654_1520981521_47712361_group_0 AS
– SELECT ROW_NUMBER() OVER() AS row_id, row_vec
– FROM mat_group_text
– WHERE matrix_id_text=1
–
– CONTEXT: Traceback (most recent call last):
– PL/Python function "pca_train", line 23, in <module>
– return pca.pca(**globals())
– PL/Python function "pca_train", line 87, in pca
– PL/Python function "pca_train", line 235, in pca_wrap
– PL/Python function "pca_train"
– ********** Error **********
–
– ERROR: plpy.SPIError: plpy.SPIError: operator does not exist: text = integer
– SQL state: 42883
– Hint: No operator matches the given name and argument type(s). You might need to add explicit type casts.
– Context: Traceback (most recent call last):
– PL/Python function "pca_train", line 23, in <module>
– return pca.pca(**globals())
– PL/Python function "pca_train", line 87, in pca
– PL/Python function "pca_train", line 235, in pca_wrap
– PL/Python function "pca_train"
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