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https://issues.apache.org/jira/browse/HADOOP-2085?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#action_12540319
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Chris Douglas commented on HADOOP-2085:
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I don't know if this is helpful, but: as it exists now, the framework is
incapable of finer granularity than an InputFormat, but neither will it object
whatever you can fit into that framework.
What you describe- directories as pseudo-tables with files as partitions-
sounds like exactly what this is geared toward.
As an example of a workaround/partial fit, consider your 16/32 way case.
Whether it would be worthwhile/possible to express in the existing code will
depend on a few factors: if the two files you're joining in the 32-way set are
pairwise disjoint, then you can simply use an OverrideRecordReader with two
custom InputFormats (each taking one "half" of the pair) to "join" them.
However, if they're not disjoint, then you'll lose values. ^1^ Feeding the
output of that into a join with your 16 way dataset might work, but it's a bit
of a hack. You'd need to be certain of the partitions of both datasets to be
confident in your results.
Notes
1. Really, you're looking for a different implementation of
CompositeRecordReader::JoinCollector that emits values from each source in
turn, rather than emitting the cross-product; this is being considered, but may
not be in the immediate future. It's of limited use with the requirement that
each source be sorted an partitioned in the same way, unfortunately. Most
simply want to merge two sorted datasets without worrying about how they're
partitioned (HADOOP-2120).
> Map-side joins on sorted, equally-partitioned datasets
> ------------------------------------------------------
>
> Key: HADOOP-2085
> URL: https://issues.apache.org/jira/browse/HADOOP-2085
> Project: Hadoop
> Issue Type: New Feature
> Components: mapred
> Reporter: Chris Douglas
> Assignee: Chris Douglas
> Fix For: 0.16.0
>
> Attachments: 2085-2.patch, 2085-3.patch, 2085.patch
>
>
> h3. Motivation
> Given a set of sorted datasets keyed with the same class and yielding equal
> partitions, it is possible to effect a join of those datasets prior to the
> map. This could save costs in re-partitioning, sorting, shuffling, and
> writing out data required in the general case.
> h3. Interface
> The attached code offers the following interface to users of these classes.
> || property || required || value ||
> | mapred.join.expr | yes | Join expression to effect over input data |
> | mapred.join.keycomparator | no | {{WritableComparator}} class to use for
> comparing keys |
> | mapred.join.define.<ident> | no | Class mapped to identifier in join
> expression |
> The join expression understands the following grammar:
> {noformat}
> func ::= <ident>([<func>,]*<func>)
> func ::= tbl(<class>,"<path>");
> {noformat}
> Operations included in this patch are partitioned into one of two types:
> join operations emitting tuples and "multi-filter" operations emitting a
> single value from (but not necessarily included in) a set of input values.
> For a given key, each operation will consider the cross product of all
> values for all sources at that node.
> Identifiers supported by default:
> || identifier || type || description ||
> | inner | Join | Full inner join |
> | outer | Join | Full outer join |
> | override | MultiFilter | For a given key, prefer values from the rightmost
> source |
> A user of this class must set the {{InputFormat}} for the job to
> {{CompositeInputFormat}} and define a join expression accepted by the
> preceding
> grammar. For example, both of the following are acceptable:
> {noformat}
> inner(tbl(org.apache.hadoop.mapred.SequenceFileInputFormat.class,
> "hdfs://host:8020/foo/bar"),
> tbl(org.apache.hadoop.mapred.SequenceFileInputFormat.class,
> "hdfs://host:8020/foo/baz"))
> outer(override(tbl(org.apache.hadoop.mapred.SequenceFileInputFormat.class,
> "hdfs://host:8020/foo/bar"),
> tbl(org.apache.hadoop.mapred.SequenceFileInputFormat.class,
> "hdfs://host:8020/foo/baz")),
> tbl(org.apache.hadoop.mapred/SequenceFileInputFormat.class,
> "hdfs://host:8020/foo/rab"))
> {noformat}
> {{CompositeInputFormat}} includes a handful of convenience methods to aid
> construction of these verbose statements.
> As in the second example, joins may be nested. Users may provide a
> comparator class in the {{mapred.join.keycomparator}} property to
> specify the ordering of their keys, or accept the default comparator as
> returned by {{WritableComparator.get(keyclass)}}.
> Users can specify their own join operations, typically by overriding
> {{JoinRecordReader}} or {{MultiFilterRecordReader}} and mapping that class
> to an identifier in the join expression using the
> {{mapred.join.define._ident_}} property, where _ident_ is the identifier
> appearing in the join expression. Users may elect to emit- or modify- values
> passing through their join operation. Consulting the existing operations for
> guidance is recommended. Adding arguments is considerably more complex (and
> only partially supported), as one must also add a {{Node}} type to the parse
> tree. One is probably better off extending {{RecordReader}} in most cases.
> h3. Design
> As alluded to above, the design defines inner (Composite) and leaf (Wrapped)
> types for the join tree. Delegation satisfies most requirements of the
> {{InputFormat}} contract, particularly {{validateInput}} and {{getSplits}}.
> Most of the work in this patch concerns {{getRecordReader}}. The
> {{CompositeInputFormat}} itself delegates to the parse tree generated by
> {{Parser}}.
> h4. Hierarchical Joins
> Each {{RecordReader}} from the user must be "wrapped", since effecting a
> join requires the framework to track the head value from each source. Since
> the cross product of all values for each composite level of the join is
> emitted to its parent, all sources ^1^ must be capable of repeating the
> values for the current key. To avoid keeping an excessive number of copies
> (one per source per level), each composite requests its children to populate
> a {{JoinCollector}} with an iterator over its values. This way, there is
> only one copy of the current key for each composite node, the head key-value
> pair for each leaf, and storage at each leaf for all the values matching the
> current key at the parent collector (if it is currently participating in a
> join at the root). Strategies have been employed to avoid excessive copying
> when filling a user-provided {{Writable}}, but they have been conservative
> (e.g. in {{MultiFilterRecordReader}}, the value emitted is cloned in case
> the user modifies the value returned, possibly changing the state of a
> {{JoinCollector}} in the tree). For example, if the following sources
> contain these key streams:
> {noformat}
> A: 0 0 1 1 2 ...
> B: 1 1 1 1 2 ...
> C: 1 6 21 107 ...
> D: 6 28 496 8128 33550336 ...
> {noformat}
> Let _A-D_ be wrapped sources and _x,y_ be composite operations. If the
> expression is of the form {{x(A, y(B,C,D))}}, then when the current key at
> the root is 1 the tree may look like this:
> {noformat}
> x (1, [ I(A), [ I(y) ] ] )
> / \
> W y (1, [ I(B), I(C), EMPTY ])
> | / | \
> | W W W
> | | | D (6, V~6~) => EMPTY
> | | C (6, V~6~) => V~1.1~ @1.1
> | B (2, V~2~) => V~1,1~ V~1,2~ V~1,3~ V~1,4~ @1,3
> A (2, V~2~) => V~1,1~ V~1,2~ @1,2
> {noformat}
> A {{JoinCollector}} from _x_ will have been created by requesting an
> iterator from _A_ and another from _y_. The iterator at _y_ is built by
> requesting iterators from _B_, _C_, and _D_. Since _D_ doesn't contain the
> key 1, it returns an empty iterator. Since the value to return for a given
> join is a {{Writable}} provided by the user, the iterators returned are also
> responsible for writing the next value in that stream. For multilevel joins
> passing through a subclass of {{JoinRecordReader}}, the value produced will
> contain tuples within tuples; iterators for composites delegate to
> sub-iterators responsible for filling the value in the tuple at the position
> matching their position in the composite. In a sense, the only iterators
> that write to a tuple are the {{RecordReader}} s at the leaves. Note that
> this also implies that emitted tuples may not contain values from each
> source, but they will always have the same capacity.
> h4. Writables
> {{Writable}} objects- including {{InputSplit}} s and {{TupleWritable}} s-
> encode themselves in the following format:
> {noformat}
> <count><class1><class2>...<classn><obj1><obj2>...<objn>
> {noformat}
> The inefficiency is regrettable- particularly since this overhead is
> incurred for every instance and most often the tuples emitted will be
> processed only within the map- but the encoding satisfies the {{Writable}}
> contract well enough to be emitted to the reducer, written to disk, etc. It
> is hoped that general compression will trim the most egregious waste. It
> should be noted that the framework does not actually write out a tuple (i.e.
> does not suffer for this deficiency) unless emitting one from
> {{MultiFilterRecordReader}} (a rare case in practice, it is hoped).
> h4. Extensibility
> The join framework is modestly extensible. Practically, users seeking to add
> their own identifiers to join expressions are limited to extending
> {{JoinRecordReader}} and {{MultiFilterRecordReader}}. There is considerable
> latitude within these constraints, as illustrated in
> {{OverrideRecordReader}}, where values in child {{RecordReader}} s are
> skipped instead of incurring the overhead of building the iterator (that
> will inevitably be discarded).^2^ For most cases, the user need only
> implement the combine and/or emit methods in their subclass. It is expected
> that most will find that the three default operations will suffice.
> Adding arguments to expressions is more difficult. One would need to include
> a {{Node}} type for the parser, which requires some knowledge of its inner
> workings. The model in this area is crude and requires refinement before it
> can be "extensible" by a reasonable definition.
> h3. Performance
> I have no numbers.
> Notes
> 1. This isn't strictly true. The "leftmost" source will never need to repeat
> itself. Adding a pseudo-{{ResettableIterator}} to handle this case would be
> a welcome addition.
> 2. Note that- even if reset- the override will only loop through the values
> in the rightmost key, instead of repeating that series a number of times
> equal to the cardinality of the cross product of the discarded streams
> (regrettably, looking at the code of {{OverrideRecordReader}} is more
> illustrative than this explanation).
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