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https://issues.apache.org/jira/browse/FLINK-2186?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17323738#comment-17323738
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Flink Jira Bot commented on FLINK-2186:
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This issue is assigned but has not received an update in 7 days so it has been
labeled "stale-assigned". If you are still working on the issue, please give an
update and remove the label. If you are no longer working on the issue, please
unassign so someone else may work on it. In 7 days the issue will be
automatically unassigned.
> 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: API / Scala, Library / Machine Learning
> Reporter: Theodore Vasiloudis
> Assignee: Anton Solovev
> Priority: Major
> Labels: pull-request-available, stale-assigned
> Time Spent: 10m
> Remaining Estimate: 0h
>
> 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.
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