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Posted to issues@arrow.apache.org by "Dominic Dennenmoser (Jira)" <ji...@apache.org> on 2020/05/09 18:43:00 UTC
[jira] [Created] (ARROW-8748) Implementing methodes for combining
arrow tabels using dplyr::bind_rows and dplyr::bind_cols
Dominic Dennenmoser created ARROW-8748:
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Summary: Implementing methodes for combining arrow tabels using dplyr::bind_rows and dplyr::bind_cols
Key: ARROW-8748
URL: https://issues.apache.org/jira/browse/ARROW-8748
Project: Apache Arrow
Issue Type: New Feature
Components: R
Reporter: Dominic Dennenmoser
First at all, many thanks for your hard work! I was quite exited, when you guys implemented some basic function of the the {{dplyr}} package. Is there a why to combine tow or more arrow tables into one by rows or columns? At the moment my workaround looks like this:
{code:r}
dplyr::bind_rows(
"a" = arrow.table.1 %>% dplyr::collect(),
"b" = arrow.table.2 %>% dplyr::collect(),
"c" = arrow.table.3 %>% dplyr::collect(),
"d" = arrow.table.4 %>% dplyr::collect(),
.id = "ID"
) %>%
arrow::write_ipc_stream(sink = "file_name_combined_tables.arrow")
{code}
But this is actually not really a meaningful measure because of putting the data back as dataframes/tibbles into the r environment, which might lead to an exhaust of RAM space. Perhaps you might have a better workaround on hand. It would be great if you guys could implement the {{bind_rows}} and {{bind_cols}} methods provided by {{dplyr}}.
{code:java}
dplyr::bind_rows(
"a" = arrow.table.1,
"b" = arrow.table.2,
"c" = arrow.table.3,
"d" = arrow.table.4,
.id = "ID"
) %>%
arrow::write_ipc_stream(sink = "file_name_combined_tables.arrow"){code}
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