Github user decibel commented on a diff in the pull request: https://github.com/apache/incubator-madlib/pull/47#discussion_r67943517 --- Diff: src/ports/postgres/modules/utilities/pivot.py_in --- @@ -0,0 +1,201 @@ +# coding=utf-8 +# +# 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. + +# Pivoting +# The goal of the MADlib pivot function is to provide a data summarization tool +# that can do basic OLAP type operations on data stored in one table and output +# the summarized data to a second table. Typical operations are count, average, +# min, max and standard deviation, however user defined aggregates (UDAs) are +# also be allowed. + +# Please refer to the pivot.sql_in file for the documentation + +""" +@file pivot.py_in + +""" +import plpy +from utilities import _assert +from utilities import split_quoted_delimited_str +from utilities import strip_end_quotes +from validate_args import table_exists +from validate_args import columns_exist_in_table +from validate_args import table_is_empty +from validate_args import _get_table_schema_names +from validate_args import get_first_schema + +m4_changequote(`<!', `!>') + +def pivot(schema_madlib, source_table, out_table, + index, pivot_cols, pivot_values, + aggregate_func, **kwargs): + """ + Helper function that can be used to pivot tables + Args: + @param source_table The original data table + @param out_table The output table that contains the dummy + variable columns + @param index The index columns to group by the records by + @param pivot_cols The columns to pivot the table + @param pivot_values The value columns to be summarized in the + pivoted table + @param aggregate_func The aggregate function to be applied to the + values + + """ + indices = split_quoted_delimited_str(index) + pcols = split_quoted_delimited_str(pivot_cols) + pvals = split_quoted_delimited_str(pivot_values) + # aggregate_func = "sum" + validate_pivot_coding(source_table, out_table, indices, pcols, pvals) + new_col_names =[] + sql_list = ["CREATE TABLE " + out_table + " AS (SELECT " + index] + # Preperation for multiple index, pivot, etc. + for pcol in pcols: + for pval in pvals: + pcol_no_quotes = strip_end_quotes(pcol.strip()) + pval_no_quotes = strip_end_quotes(pval.strip()) + distinct_values = plpy.execute( + "SELECT {pcol} AS value FROM {source_table} " + "GROUP BY {pcol} ORDER BY {pcol}". + format(pcol=pcol, source_table=source_table)) + distinct_values = [strip_end_quotes(item['value']) for item in distinct_values] --- End diff -- I'm not sure what strip_end_quotes does, but I suspect what you want to be doing here is using quote_ident(). You could incorporate it into the distinct values query: `SELECT *, quote_ident(column1_values) AS column1_quoted, quote_ident(column2_values) AS column2_quoted FROM (<distinct query above>) d;`
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