[
https://issues.apache.org/jira/browse/FLINK-2186?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15027369#comment-15027369
]
Chesnay Schepler commented on FLINK-2186:
-----------------------------------------
that's true. what about shorthands for classes then?
{code:title=CsvReader}
public static final Class<String> S = String.class;
public static final Class<Integer> I = Integer.class;
{code}
then the following lines would be equivalent:
{code:title=usercode}
env.readCsvFile(<path>).types(String.class, Integer.class, String.class);
env.readCsvFile(<path>).types(S, I, S);
{code}
> Rework CSV import to support very wide files
> --------------------------------------------
>
> Key: FLINK-2186
> URL: https://issues.apache.org/jira/browse/FLINK-2186
> Project: Flink
> Issue Type: Improvement
> Components: Machine Learning Library, Scala API
> Reporter: Theodore Vasiloudis
>
> In the current readVcsFile implementation, importing CSV files with many
> columns can become from cumbersome to impossible.
> For example to import an 11 column file we need to write:
> {code}
> val cancer = env.readCsvFile[(String, String, String, String, String, String,
> String, String, String, String,
> String)]("/path/to/breast-cancer-wisconsin.data")
> {code}
> For many use cases in Machine Learning we might have CSV files with thousands
> or millions of columns that we want to import as vectors.
> In that case using the current readCsvFile method becomes impossible.
> We therefore need to rework the current function, or create a new one that
> will allow us to import CSV files with an arbitrary number of columns.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
