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https://issues.apache.org/jira/browse/ORC-161?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16434889#comment-16434889
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ASF GitHub Bot commented on ORC-161:
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Github user t3rmin4t0r commented on a diff in the pull request:
https://github.com/apache/orc/pull/245#discussion_r180957651
--- Diff: site/_docs/encodings.md ---
@@ -123,6 +127,41 @@ DIRECT_V2 | PRESENT | Yes | Boolean
RLE
| DATA | No | Unbounded base 128 varints
| SECONDARY | No | Unsigned Integer RLE v2
+In ORC 2.0, DECIMAL and DECIMAL_V2 encodings are introduced and scale
+stream is totally removed as all decimal values use the same scale.
+There are two difference cases: precision<=18 and precision>18.
+
+### Decimal Encoding for precision <= 18
+
+When precision is no greater than 18, decimal values can be fully
+represented by 64-bit signed integers which are stored in DATA stream
+and use signed integer RLE.
+
+Encoding | Stream Kind | Optional | Contents
+:------------ | :-------------- | :------- | :-------
+DECIMAL | PRESENT | Yes | Boolean RLE
+ | DATA | No | Signed Integer RLE v1
+DECIMAL_V2 | PRESENT | Yes | Boolean RLE
+ | DATA | No | Signed Integer RLE v2
+
+### Decimal Encoding for precision > 18
+
+When precision is greater than 18, decimal value is split into two
+parts: a signed integer stores higher 64 bits and an unsigned integer
+stores lower 64 bits. Therefore, a DATA stream is utilized to store
+the higher 64-bit signed integer of decimal values and a SECONDARY
+stream holds the lower 64-bit unsigned integer of decimal values.
+Both streams use RLE and are not optional in this case.
+
+Encoding | Stream Kind | Optional | Contents
+:------------ | :-------------- | :------- | :-------
+DECIMAL | PRESENT | Yes | Boolean RLE
--- End diff --
This is when Decimal v1 can be retired from the encodings.
> Create a new column type that run-length-encodes decimals
> ---------------------------------------------------------
>
> Key: ORC-161
> URL: https://issues.apache.org/jira/browse/ORC-161
> Project: ORC
> Issue Type: Wish
> Components: encoding
> Reporter: Douglas Drinka
> Priority: Major
>
> I'm storing prices in ORC format, and have made the following observations
> about the current decimal implementation:
> - The encoding is inefficient: my prices are a walking-random set, plus or
> minus a few pennies per data point. This would encode beautifully with a
> patched base encoding. Instead I'm averaging 4 bytes per data point, after
> Zlib.
> - Everyone acknowledges that it's nice to be able to store huge numbers in
> decimal columns, but that you probably won't. Presto, for instance, has a
> fast-path which engages for precision of 18 or less, and decodes to 64-bit
> longs, and then a slow path which uses BigInt. I anticipate the majority of
> implementations fit the decimal(18,6) use case.
> - The whole concept of precision/scale, along with a dedicated scale per data
> point is messy. Sometimes it's checked on data ingest, other times its an
> error on reading, or else it's cast (and rounded?)
> I don't propose eliminating the current column type. It's nice to know
> there's a way to store really big numbers (or really accurate numbers) if I
> need that in the future.
> But I'd like to see a new column that uses the existing Run Length Encoding
> functionality, and is limited to 63+1 bit numbers, with a fixed precision and
> scale for ingest and query.
> I think one could call this FixedPoint. Every number is stored as a long,
> and scaled by a column constant. Ingest from decimal would scale and throw
> or round, configurably. Precision would be fixed at 18, or made configurable
> and verified at ingest. Stats would use longs (scaled with the column)
> rather than strings.
> Anyone can opt in to faster, smaller data sets, if they're ok with 63+1 bits
> of precision. Or they can keep using decimal if they need 128 bits. Win/win?
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