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https://issues.apache.org/jira/browse/PIG-1295?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Gianmarco De Francisci Morales updated PIG-1295:
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Attachment: PIG-1295_0.9.patch
Implemented a new compareBinInterSedesTuple() method.
This new method works with data serialized with [PIG-1472] format.
It relies on DataType for data type comparison by translating the data types.
I implemented some logic to read unsinged ints from bytes and shorts because I
am using ByteBuffer that does not implement the DataInput interface. We might
want to change that later.
For now complex data types cause the whole tuple to be deserialized, but I have
put some placeholders for methods to deserialize single complex objects and
continue the normal execution flow.
I plan to fill them in when I move the code inside BinInterSedes so that I can
use the methods to read complex data types (readBag, readMap, etc..). This will
involve some juggling around between DataInputBuffer and ByteBuffer (this is
why we might consider to switch out ByteBuffer) to get the cursors consistent
among them.
I think the next step would be splitting the comparator and putting it into the
serialization class (BinInterSedes). I don't know yet how to modify the class
interface to make the comparator class available outside (but I think this
relates to phase 2).
I see no good place to put the class that implements the comparator for
DefaultTuple, and Daniel said it is a minor case, so should I just throw away
the code for DefaultTuple?
> Binary comparator for secondary sort
> ------------------------------------
>
> Key: PIG-1295
> URL: https://issues.apache.org/jira/browse/PIG-1295
> Project: Pig
> Issue Type: Improvement
> Components: impl
> Affects Versions: 0.7.0
> Reporter: Daniel Dai
> Assignee: Gianmarco De Francisci Morales
> Fix For: 0.8.0
>
> Attachments: PIG-1295_0.1.patch, PIG-1295_0.2.patch,
> PIG-1295_0.3.patch, PIG-1295_0.4.patch, PIG-1295_0.5.patch,
> PIG-1295_0.6.patch, PIG-1295_0.7.patch, PIG-1295_0.8.patch, PIG-1295_0.9.patch
>
>
> When hadoop framework doing the sorting, it will try to use binary version of
> comparator if available. The benefit of binary comparator is we do not need
> to instantiate the object before we compare. We see a ~30% speedup after we
> switch to binary comparator. Currently, Pig use binary comparator in
> following case:
> 1. When semantics of order doesn't matter. For example, in distinct, we need
> to do a sort in order to filter out duplicate values; however, we do not care
> how comparator sort keys. Groupby also share this character. In this case, we
> rely on hadoop's default binary comparator
> 2. Semantics of order matter, but the key is of simple type. In this case, we
> have implementation for simple types, such as integer, long, float,
> chararray, databytearray, string
> However, if the key is a tuple and the sort semantics matters, we do not have
> a binary comparator implementation. This especially matters when we switch to
> use secondary sort. In secondary sort, we convert the inner sort of nested
> foreach into the secondary key and rely on hadoop to sorting on both main key
> and secondary key. The sorting key will become a two items tuple. Since the
> secondary key the sorting key of the nested foreach, so the sorting semantics
> matters. It turns out we do not have binary comparator once we use secondary
> sort, and we see a significant slow down.
> Binary comparator for tuple should be doable once we understand the binary
> structure of the serialized tuple. We can focus on most common use cases
> first, which is "group by" followed by a nested sort. In this case, we will
> use secondary sort. Semantics of the first key does not matter but semantics
> of secondary key matters. We need to identify the boundary of main key and
> secondary key in the binary tuple buffer without instantiate tuple itself.
> Then if the first key equals, we use a binary comparator to compare secondary
> key. Secondary key can also be a complex data type, but for the first step,
> we focus on simple secondary key, which is the most common use case.
> We mark this issue to be a candidate project for "Google summer of code 2010"
> program.
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