ASF GitHub Bot commented on ORC-161:

Github user t3rmin4t0r commented on a diff in the pull request:

    --- Diff: site/_docs/encodings.md ---
    @@ -109,10 +109,20 @@ DIRECT_V2     | PRESENT         | Yes      | Boolean 
     Decimal was introduced in Hive 0.11 with infinite precision (the total
     number of digits). In Hive 0.13, the definition was change to limit
     the precision to a maximum of 38 digits, which conveniently uses 127
    -bits plus a sign bit. The current encoding of decimal columns stores
    -the integer representation of the value as an unbounded length zigzag
    -encoded base 128 varint. The scale is stored in the SECONDARY stream
    -as an signed integer.
    +bits plus a sign bit.
    +DIRECT and DIRECT_V2 encodings of decimal columns stores the integer
    +representation of the value as an unbounded length zigzag encoded base
    +128 varint. The scale is stored in the SECONDARY stream as an signed
    +In ORC 2.0, DECIMAL encoding is introduced and totally remove scale
    +stream as all decimal values use the same scale. When precision is
    +no greater than 18, decimal values can be fully represented by DATA
    +stream which stores 64-bit signed integers. When precision is greater
    +than 18, we use a 128-bit signed integer to store the decimal value.
    +DATA stream stores the higher 64 bits and SECONDARY stream holds the
    +lower 64 bits. Both streams use signed integer RLE v2.
    --- End diff --
    The multiple-stream + row-group stride problems for IO were discussed by 
    The disk layout is what matters for IO, not the logical stream separation.

> 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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