[
https://issues.apache.org/jira/browse/MADLIB-1240?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Frank McQuillan updated MADLIB-1240:
------------------------------------
Description:
related to https://issues.apache.org/jira/browse/MADLIB-1239
Vector to Columns
Converts a feature array in a single column of an output table into multiple
columns. This process can be used to reverse the function cols2vec.
{code}
vec2cols(
source_table,
out_table,
vector_col,
dictionary,
cols_to_output
)
source_table
TEXT. Name of the table containing the source data.
out_table
TEXT. Name of the generated table containing the output. If a table with the
same name already exists, an error will be returned.
vector_col
TEXT. Name of the column containing the feature array. Must be a
one-dimensional array.
dictionary (optional)
TEXT. Name of the table containing the array of names associated with the
feature array. This table is created by the function 'cols2vec'. If the
dictionary table is not specified, column names will be automatically generated
of the form 'feature_1, feature_2, ...feature_n'
cols_to_output (optional)
TEXT, default NULL. Comma-separated string of column names from the source
table to keep in the output table, in addition to the feature columns. To keep
all columns from the source table, use '*'.
Output
The output table produced by the vec2cols function contains the following
columns:
<...>
Columns from source table, depending on which ones are kept (if any).
feature columns
Columns for each of the features in 'vector_col'. Column type will depend on
the feature array type in the source table. Column naming will depend on
whether the parameter 'dictionary' is used.
{code}
Notes
(1)
The function
http://pivotalsoftware.github.io/PDLTools/group__ArrayUtilities.html
is similar but the proposed MADlib one has more options. To do the equivalent
of the PDL Tools one in MADlib, you would do:
{code}
vec2cols(
table_name,
output_table,
vector_column,
NULL,
'*'
)
{code}
(2)
Please put the generated feature columns on the right side of the output table,
i.e., they will be the last column on the right. Maintain the order of the
array.
was:
Vector to Columns
Converts a feature array in a single column of an output table into multiple
columns. This process can be used to reverse the function cols2vec.
{code}
vec2cols(
source_table,
out_table,
vector_col,
dictionary,
cols_to_output
)
source_table
TEXT. Name of the table containing the source data.
out_table
TEXT. Name of the generated table containing the output. If a table with the
same name already exists, an error will be returned.
vector_col
TEXT. Name of the column containing the feature array. Must be a
one-dimensional array.
dictionary (optional)
TEXT. Name of the table containing the array of names associated with the
feature array. This table is created by the function 'cols2vec'. If the
dictionary table is not specified, column names will be automatically generated
of the form 'feature_1, feature_2, ...feature_n'
cols_to_output (optional)
TEXT, default NULL. Comma-separated string of column names from the source
table to keep in the output table, in addition to the feature columns. To keep
all columns from the source table, use '*'.
Output
The output table produced by the vec2cols function contains the following
columns:
<...>
Columns from source table, depending on which ones are kept (if any).
feature columns
Columns for each of the features in 'vector_col'. Column type will depend on
the feature array type in the source table. Column naming will depend on
whether the parameter 'dictionary' is used.
{code}
Notes
(1)
The function
http://pivotalsoftware.github.io/PDLTools/group__ArrayUtilities.html
is similar but the proposed MADlib one has more options. To do the equivalent
of the PDL Tools one in MADlib, you would do:
{code}
vec2cols(
table_name,
output_table,
vector_column,
NULL,
'*'
)
{code}
(2)
Please put the generated feature columns on the right side of the output table,
i.e., they will be the last column on the right. Maintain the order of the
array.
> Vector to Columns
> -----------------
>
> Key: MADLIB-1240
> URL: https://issues.apache.org/jira/browse/MADLIB-1240
> Project: Apache MADlib
> Issue Type: New Feature
> Components: Module: Utilities
> Reporter: Frank McQuillan
> Priority: Major
> Fix For: v1.15
>
>
> related to https://issues.apache.org/jira/browse/MADLIB-1239
> Vector to Columns
> Converts a feature array in a single column of an output table into multiple
> columns. This process can be used to reverse the function cols2vec.
> {code}
> vec2cols(
> source_table,
> out_table,
> vector_col,
> dictionary,
> cols_to_output
> )
> source_table
> TEXT. Name of the table containing the source data.
> out_table
> TEXT. Name of the generated table containing the output. If a table with the
> same name already exists, an error will be returned.
> vector_col
> TEXT. Name of the column containing the feature array. Must be a
> one-dimensional array.
> dictionary (optional)
> TEXT. Name of the table containing the array of names associated with the
> feature array. This table is created by the function 'cols2vec'. If the
> dictionary table is not specified, column names will be automatically
> generated of the form 'feature_1, feature_2, ...feature_n'
> cols_to_output (optional)
> TEXT, default NULL. Comma-separated string of column names from the source
> table to keep in the output table, in addition to the feature columns. To
> keep all columns from the source table, use '*'.
> Output
> The output table produced by the vec2cols function contains the following
> columns:
> <...>
> Columns from source table, depending on which ones are kept (if any).
> feature columns
> Columns for each of the features in 'vector_col'. Column type will depend on
> the feature array type in the source table. Column naming will depend on
> whether the parameter 'dictionary' is used.
> {code}
> Notes
> (1)
> The function
> http://pivotalsoftware.github.io/PDLTools/group__ArrayUtilities.html
> is similar but the proposed MADlib one has more options. To do the
> equivalent of the PDL Tools one in MADlib, you would do:
> {code}
> vec2cols(
> table_name,
> output_table,
> vector_column,
> NULL,
> '*'
> )
> {code}
> (2)
> Please put the generated feature columns on the right side of the output
> table, i.e., they will be the last column on the right. Maintain the order
> of the array.
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