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From "Daniel Dai (JIRA)" <j...@apache.org>
Subject [jira] Commented: (PIG-1295) Binary comparator for secondary sort
Date Wed, 04 Aug 2010 00:05:17 GMT

    [ https://issues.apache.org/jira/browse/PIG-1295?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12895093#action_12895093
] 

Daniel Dai commented on PIG-1295:
---------------------------------

Hi, Gianmarco,
1. Notice currently PigTupleRawComparator is only used in "order-by" job, PigSecondaryKeyComparator
only used by "non-order-by" job, there is a semantic difference in null handling. In order-by,
different null key are treated equal; In group-by, however, null from different relation cannot
merge (this is to conform with SQL standard). In your case, RawTupleComparator can be used
in both "order-by tuple" case and "non-order-by" with secondary key case. So there will be
semantic gap between this two. We need to deal with it separately. For simplicity, we can
focus on secondary key case first (which means, different null keys from different relations
are not equal)

2. We need to deal with sort order. When we use PigTupleRawComparator for secondary sort,
it's quite clear the structure will be (main_key, secondary_key, value). I think we can limit
PigTupleRawComparator specific to this structure currently (don't think about order-by tuple
case), so you can pass the sort order and deal with it in PigTupleRawComparator

3. Yes, I think it might be better to keep mIndex/mNull handling outside RawTupleComparator

> 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_0.10.patch, PIG-1295_0.11.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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