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https://issues.apache.org/jira/browse/ARROW-1957?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16310234#comment-16310234
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Jordan Samuels commented on ARROW-1957:
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[~wesmckinn] Thanks for your response and explanation. I'm still not clear on
*why* nanosecond resolution timestamps are deprecated - is that for performance
reasons? What are the medium-/long-term ramifications of using the deprecated
option you mention?
> Handle nanosecond timestamps in parquet serialization
> -----------------------------------------------------
>
> Key: ARROW-1957
> URL: https://issues.apache.org/jira/browse/ARROW-1957
> Project: Apache Arrow
> Issue Type: Improvement
> Affects Versions: 0.8.0
> Environment: Python 3.6.4. Mac OSX and CentOS Linux release
> 7.3.1611. Pandas 0.21.1 .
> Reporter: Jordan Samuels
> Priority: Minor
>
> The following code
> {code}
> import pyarrow as pa
> import pyarrow.parquet as pq
> import pandas as pd
> n=3
> df = pd.DataFrame({'x': range(n)}, index=pd.DatetimeIndex(start='2017-01-01',
> freq='1n', periods=n))
> pq.write_table(pa.Table.from_pandas(df), '/tmp/t.parquet'){code}
> results in:
> {{ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data:
> 1483228800000000001}}
> The desired effect is that we can save nanosecond resolution without losing
> precision (e.g. conversion to ms). Note that if {{freq='1u'}} is used, the
> code runs properly.
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