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HBASE-19182 Add deprecation in branch-1 for hbase-prefix-tree so some heads up it removed in hbase2

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Michael Stack 2017-11-04 10:37:10 -07:00
parent ca68d77862
commit 045c02d178
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3 changed files with 9 additions and 3 deletions
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2
hbase-prefix-tree/pom.xml
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@ -29,7 +29,7 @@
<artifactId>hbase-prefix-tree</artifactId> <artifactId>hbase-prefix-tree</artifactId>
<name>Apache HBase - Prefix Tree</name> <name>Apache HBase - Prefix Tree</name>
<description>Prefix Tree Data Block Encoder</description> <description>Prefix Tree Data Block Encoder; DEPRECATED! Removed in hbase-2.0.0</description>
<build> <build>
<plugins> <plugins>

3
hbase-prefix-tree/src/main/java/org/apache/hadoop/hbase/codec/prefixtree/PrefixTreeCodec.java
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@ -57,7 +57,10 @@ import org.apache.hadoop.io.WritableUtils;
* {@link PrefixTreeEncoder}, and decoding is delegated to instances of * {@link PrefixTreeEncoder}, and decoding is delegated to instances of
* {@link org.apache.hadoop.hbase.codec.prefixtree.scanner.CellSearcher}. Encoder and decoder instances are * {@link org.apache.hadoop.hbase.codec.prefixtree.scanner.CellSearcher}. Encoder and decoder instances are
* created and recycled by static PtEncoderFactory and PtDecoderFactory. * created and recycled by static PtEncoderFactory and PtDecoderFactory.
* @deprecated Since 1.2.7. Will be removed in 2.0.0. Write the dev list if you would like to take on the
* maintainence of this facility.
*/ */
@Deprecated
@InterfaceAudience.Private @InterfaceAudience.Private
public class PrefixTreeCodec implements DataBlockEncoder{ public class PrefixTreeCodec implements DataBlockEncoder{

7
src/main/asciidoc/_chapters/compression.adoc
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@ -115,13 +115,16 @@ The data format is nearly identical to Diff encoding, so there is not an image t
Prefix Tree:: Prefix Tree::
Prefix tree encoding was introduced as an experimental feature in HBase 0.96. Prefix tree encoding was introduced as an experimental feature in HBase 0.96.
It provides similar memory savings to the Prefix, Diff, and Fast Diff encoder, but provides faster random access at a cost of slower encoding speed. It provides similar memory savings to the Prefix, Diff, and Fast Diff encoder, but provides faster random access at a cost of slower encoding speed.
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Prefix Tree may be appropriate for applications that have high block cache hit ratios. It introduces new 'tree' fields for the row and column. Prefix Tree may be appropriate for applications that have high block cache hit ratios. It introduces new 'tree' fields for the row and column.
The row tree field contains a list of offsets/references corresponding to the cells in that row. This allows for a good deal of compression. The row tree field contains a list of offsets/references corresponding to the cells in that row. This allows for a good deal of compression.
For more details about Prefix Tree encoding, see link:https://issues.apache.org/jira/browse/HBASE-4676[HBASE-4676]. For more details about Prefix Tree encoding, see link:https://issues.apache.org/jira/browse/HBASE-4676[HBASE-4676].
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It is difficult to graphically illustrate a prefix tree, so no image is included. See the Wikipedia article for link:http://en.wikipedia.org/wiki/Trie[Trie] for more general information about this data structure. It is difficult to graphically illustrate a prefix tree, so no image is included. See the Wikipedia article for link:http://en.wikipedia.org/wiki/Trie[Trie] for more general information about this data structure.
Prefix Tree will be removed in hbase-2.0.0. It is a sweet feature but has seen little uptake and is not actively maintained.
Come and write the dev list if you are interesting in carrying-on this encoding.
=== Which Compressor or Data Block Encoder To Use === Which Compressor or Data Block Encoder To Use
The compression or codec type to use depends on the characteristics of your data. Choosing the wrong type could cause your data to take more space rather than less, and can have performance implications. The compression or codec type to use depends on the characteristics of your data. Choosing the wrong type could cause your data to take more space rather than less, and can have performance implications.