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https://issues.apache.org/jira/browse/HIVE-18098?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Eugene Koifman updated HIVE-18098:
----------------------------------
Description:
How should this work?
For regular tables export just copies the files under table root to a specified
directory.
This doesn't make sense for Acid tables:
* Some data may belong to aborted transactons
* Transaction IDs are imbedded into data/files names. You'd have export delta/
and base/ each of which may have files with the same names, e.g. bucket_00000.
* On import these IDs won't make sense in a different cluster or even a
different table (which may have delta_x_x for example for the same x (but
different data of course).
* Export creates a _metadata column types, storage format, etc. Perhaps it can
include info about aborted IDs (if the whole file can't be skipped).
* Even importing into the same table on the same cluster may be a problem. For
example delta_5_5/ existed at the time of export and was included in the
export. But 2 days later it may not exist because it was compacted and cleaned.
* If importing back into the same table on the same cluster, the data could be
imported into a different transaction (assuming per table writeIDs) w/o having
to remap the IDs in the rows themselves.
* support Import Overwrite?
* Support Import as a new txn with remapping of ROW_IDs? The new writeID can
be stored in a delta_x_x/_meta_data and ROW__IDs can be remapped at read time
(like isOriginal) and made permanent by compaction.
* It doesn't seem reasonable to import acid data into non-acid table
Perhaps import can work similar to Load Data: look at the file imported, if it
has Acid columns, leave a note in the delta_x_x/_meta_data to indicate that
these columns should be skipped a new ROW_IDs assigned at read time.
h3. Case I
Table has delta_7_7 and delta_8_8. Sine both may have bucket_0000, we could
export to export_dir and rename files as bucket_0000 and bucket_0000_copy_1.
Load Data supports input dir with copy_N files.
h3. Case II
what if we have delete_delta_9_9 in the source. Now you can't just ignore
ROW_IDs after import.
* -Only export the latest base_N? Or more generally up to the smallest deleted
ROW_ID (which may be hard to find w/o scanning all deletes. The export then
would have to be done under X lock to prevent new concurrent deletes)-
* Stash all deletes in some additional file file which on import gets added
into the target delta/ so that Acid reader can apply them to the data in this
delta/ but so that they don't clash with 'normal' deletes that exist in the
table.
** here we may also have multiple delete_delta/ with identical file names.
Does delete delta reader handle copy_N files?
was:
How should this work?
For regular tables export just copies the files under table root to a specified
directory.
This doesn't make sense for Acid tables:
* Some data may belong to aborted transactons
* Transaction IDs are imbedded into data/files names. You'd have export delta/
and base/ each of which may have files with the same names, e.g. bucket_00000.
* On import these IDs won't make sense in a different cluster or even a
different table (which may have delta_x_x for example for the same x (but
different data of course).
* Export creates a _metadata column types, storage format, etc. Perhaps it can
include info about aborted IDs (if the whole file can't be skipped).
* Even importing into the same table on the same cluster may be a problem. For
example delta_5_5/ existed at the time of export and was included in the
export. But 2 days later it may not exist because it was compacted and cleaned.
* If importing back into the same table on the same cluster, the data could be
imported into a different transaction (assuming per table writeIDs) w/o having
to remap the IDs in the rows themselves.
* support Import Overwrite?
* Support Import as a new txn with remapping of ROW_IDs? The new writeID can
be stored in a delta_x_x/_meta_data and ROW__IDs can be remapped at read time
(like isOriginal) and made permanent by compaction.
* It doesn't seem reasonable to import acid data into non-acid table
Perhaps import can work similar to Load Data: look at the file imported, if it
has Acid columns, leave a note in the delta_x_x/_meta_data to indicate that
these columns should be skipped a new ROW_IDs assigned at read time.
h3. Case I
Table has delta_7_7 and delta_8_8. Sine both may have bucket_0000, we could
export to export_dir and rename files as bucket_0000 and bucket_0000_copy_1.
Load Data supports input dir with copy_N files.
h3. Case II
what if we have delete_delta_9_9 in the source. Now you can't just ignore
ROW_IDs after import.
* Only export the latest base_N? Or more generally up to the smallest deleted
ROW_ID (which may be hard to find w/o scanning all deletes. The export then
would have to be done under X lock to prevent new concurrent deletes)
* Stash all deletes in some additional file file which on import gets added
into the target delta/ so that Acid reader can apply them to the data in this
delta/ but so that they don't clash with 'normal' deletes that exist in the
table.
** here we may also have multiple delete_delta/ with identical file names.
Does delete delta reader handle copy_N files?
> Add support for Export/Import for Acid tables
> ---------------------------------------------
>
> Key: HIVE-18098
> URL: https://issues.apache.org/jira/browse/HIVE-18098
> Project: Hive
> Issue Type: New Feature
> Components: Transactions
> Reporter: Eugene Koifman
> Assignee: Eugene Koifman
>
> How should this work?
> For regular tables export just copies the files under table root to a
> specified directory.
> This doesn't make sense for Acid tables:
> * Some data may belong to aborted transactons
> * Transaction IDs are imbedded into data/files names. You'd have export
> delta/ and base/ each of which may have files with the same names, e.g.
> bucket_00000.
> * On import these IDs won't make sense in a different cluster or even a
> different table (which may have delta_x_x for example for the same x (but
> different data of course).
> * Export creates a _metadata column types, storage format, etc. Perhaps it
> can include info about aborted IDs (if the whole file can't be skipped).
> * Even importing into the same table on the same cluster may be a problem.
> For example delta_5_5/ existed at the time of export and was included in the
> export. But 2 days later it may not exist because it was compacted and
> cleaned.
> * If importing back into the same table on the same cluster, the data could
> be imported into a different transaction (assuming per table writeIDs) w/o
> having to remap the IDs in the rows themselves.
> * support Import Overwrite?
> * Support Import as a new txn with remapping of ROW_IDs? The new writeID can
> be stored in a delta_x_x/_meta_data and ROW__IDs can be remapped at read time
> (like isOriginal) and made permanent by compaction.
> * It doesn't seem reasonable to import acid data into non-acid table
> Perhaps import can work similar to Load Data: look at the file imported, if
> it has Acid columns, leave a note in the delta_x_x/_meta_data to indicate
> that these columns should be skipped a new ROW_IDs assigned at read time.
> h3. Case I
> Table has delta_7_7 and delta_8_8. Sine both may have bucket_0000, we could
> export to export_dir and rename files as bucket_0000 and bucket_0000_copy_1.
> Load Data supports input dir with copy_N files.
> h3. Case II
> what if we have delete_delta_9_9 in the source. Now you can't just ignore
> ROW_IDs after import.
> * -Only export the latest base_N? Or more generally up to the smallest
> deleted ROW_ID (which may be hard to find w/o scanning all deletes. The
> export then would have to be done under X lock to prevent new concurrent
> deletes)-
> * Stash all deletes in some additional file file which on import gets added
> into the target delta/ so that Acid reader can apply them to the data in this
> delta/ but so that they don't clash with 'normal' deletes that exist in the
> table.
> ** here we may also have multiple delete_delta/ with identical file names.
> Does delete delta reader handle copy_N files?
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