hadoop-pig-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Gianmarco De Francisci Morales (JIRA)" <j...@apache.org>
Subject [jira] Updated: (PIG-1295) Binary comparator for secondary sort
Date Mon, 07 Jun 2010 22:11:19 GMT

     [ https://issues.apache.org/jira/browse/PIG-1295?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Gianmarco De Francisci Morales updated PIG-1295:
------------------------------------------------

    Attachment: PIG-1295_0.2.patch

I added some simple performance tests.
The tests generate 1 million tuples modifying a prototypical tuple and compare them to the
prototype.
One test uses the new comparator and the other uses the old one. I generate exactly the same
tuples using a fixed seed. I also check the correctness of the comparisons using the normal
compareTo() method of the tuples.

The logic to generate the tuples is a bit involved: I tried to exercise all the datatype comparisons
in a uniform manner, so I mutate less the first elements of the tuple, in order to have more
probability of getting the comparison further down the tuple. The probabilities are totally
made up and do not make much sense.

As a first approximation, I see a slight overall speedup in the test.
I will do some profiling to see which margins of improvement we have.

> 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: Daniel Dai
>         Attachments: PIG-1295_0.1.patch, PIG-1295_0.2.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.


-- 
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.


Mime
View raw message