[Zebra] to support record(row)-based file split in Zebra' TableInputFormat
--------------------------------------------------------------------------
Key: PIG-1077
URL: https://issues.apache.org/jira/browse/PIG-1077
Project: Pig
Issue Type: New Feature
Affects Versions: 0.4.0
Reporter: Chao Wang
Assignee: Chao Wang
Fix For: 0.6.0
TFile currently supports split by record sequence number (see Jira
HADOOP-6218). We want to utilize this to provide record(row)-based input split
support in Zebra.
One prominent benefit is that: in cases where we have very large data files, we
can create much more fine-grained input splits than before where we can only
create one big split for one big file.
In more detail, the new row-based getSplits() works by default (user does not
specify no. of splits to be generated) as follows:
1) Select the biggest column group in terms of data size, split all of its
TFiles according to hdfs block size (64 MB or 128 MB) and get a list of
physical byte offsets as the output per TFile. For example, let us assume for
the 1st TFile we get offset1, offset2, ..., offset10;
2) Invoke TFile.getRecordNumNear(long offset) to get the RecordNum of a
key-value pair near a byte offset. For the example above, say we get
recordNum1, recordNum2, ..., recordNum10;
3) Stitch [0, recordNum1], [recordNum1+1, recordNum2], ..., [recordNum9+1,
recordNum10], [recordNum10+1, lastRecordNum] splits of all column groups,
respectively to form 11 record-based input splits for the 1st TFile.
4) For each input split, we need to create a TFile scanner through:
TFile.createScannerByRecordNum(long beginRecNum, long endRecNum).
Note: conversion from byte offset to record number will be done by each mapper,
rather than being done at the job initialization phase. This is due to
performance concern since the conversion incurs some TFile reading overhead.
--
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.
