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Posted to commits@hbase.apache.org by dm...@apache.org on 2013/04/02 20:18:51 UTC
svn commit: r1463657 - in /hbase/trunk/hbase-assembly/src/docbkx:
case_studies.xml schema_design.xml
Author: dmeil
Date: Tue Apr 2 18:18:50 2013
New Revision: 1463657
URL: http://svn.apache.org/r1463657
Log:
hbase-8244. refguide. Moving list data schema design use-case to Schema Design chapter.
Modified:
hbase/trunk/hbase-assembly/src/docbkx/case_studies.xml
hbase/trunk/hbase-assembly/src/docbkx/schema_design.xml
Modified: hbase/trunk/hbase-assembly/src/docbkx/case_studies.xml
URL: http://svn.apache.org/viewvc/hbase/trunk/hbase-assembly/src/docbkx/case_studies.xml?rev=1463657&r1=1463656&r2=1463657&view=diff
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Binary files - no diff available.
Modified: hbase/trunk/hbase-assembly/src/docbkx/schema_design.xml
URL: http://svn.apache.org/viewvc/hbase/trunk/hbase-assembly/src/docbkx/schema_design.xml?rev=1463657&r1=1463656&r2=1463657&view=diff
==============================================================================
--- hbase/trunk/hbase-assembly/src/docbkx/schema_design.xml (original)
+++ hbase/trunk/hbase-assembly/src/docbkx/schema_design.xml Tue Apr 2 18:18:50 2013
@@ -431,16 +431,20 @@ public static byte[][] getHexSplits(Stri
can be approached. Note: this is just an illustration of potential approaches, not an exhaustive list.
Know your data, and know your processing requirements.
</para>
- <para>There are 3 case studies described:
+ <para>It is highly recommended that you read the rest of the <xref linkend="schema">Schema Design Chapter</xref> first, before reading
+ these case studies.
+ </para>
+ <para>Thee following case studies are described:
<itemizedlist>
<listitem>Log Data / Timeseries Data</listitem>
<listitem>Log Data / Timeseries on Steroids</listitem>
<listitem>Customer/Sales</listitem>
+ <listitem>Tall/Wide/Middle Schema Design</listitem>
+ <listitem>List Data</listitem>
</itemizedlist>
- ... and then a brief section on "Tall/Wide/Middle" in terms of schema design approaches.
</para>
<section xml:id="schema.casestudies.log-timeseries">
- <title>Log Data and Timeseries Data Case Study</title>
+ <title>Case Study - Log Data and Timeseries Data</title>
<para>Assume that the following data elements are being collected.
<itemizedlist>
<listitem>Hostname</listitem>
@@ -524,9 +528,11 @@ long bucket = timestamp % numBuckets;
</section> <!-- varkeys -->
</section> <!-- log data and timeseries -->
<section xml:id="schema.casestudies.log-timeseries.log-steroids">
- <title>Log Data and Timeseries Data on Steroids Case Study</title>
+ <title>Case Study - Log Data and Timeseries Data on Steroids</title>
<para>This effectively is the OpenTSDB approach. What OpenTSDB does is re-write data and pack rows into columns for
- certain time-periods. For a detailed explanation, see: <link xlink:href="http://opentsdb.net/schema.html">http://opentsdb.net/schema.html</link>.
+ certain time-periods. For a detailed explanation, see: <link xlink:href="http://opentsdb.net/schema.html">http://opentsdb.net/schema.html</link>,
+ and <link xlink:href="http://www.cloudera.com/content/cloudera/en/resources/library/hbasecon/video-hbasecon-2012-lessons-learned-from-opentsdb.html">Lessons Learned from OpenTSDB</link>
+ from HBaseCon2012.
</para>
<para>But this is how the general concept works: data is ingested, for example, in this mannerâ¦
<programlisting>
@@ -544,7 +550,7 @@ long bucket = timestamp % numBuckets;
</section> <!-- log data timeseries steroids -->
<section xml:id="schema.casestudies.log-timeseries.custsales">
- <title>Customer / Sales Case Study</title>
+ <title>Case Study - Customer / Sales</title>
<para>Assume that HBase is used to store customer and sales information. There are two core record-types being ingested:
a Customer record type, and Sales record type.
</para>
@@ -612,7 +618,7 @@ reasonable spread in the keyspace, simil
</para>
</section>
</section> <!-- cust/sales -->
- <section xml:id="schema.smackdown"><title>"Tall/Wide/Middle" Schema Design Smackdown</title>
+ <section xml:id="schema.smackdown"><title>Case Study - "Tall/Wide/Middle" Schema Design Smackdown</title>
<para>This section will describe additional schema design questions that appear on the dist-list, specifically about
tall and wide tables. These are general guidelines and not laws - each application must consider its own needs.
</para>
@@ -638,11 +644,145 @@ reasonable spread in the keyspace, simil
OpenTSDB is the best example of this case where a single row represents a defined time-range, and then discrete events are treated as
columns. This approach is often more complex, and may require the additional complexity of re-writing your data, but has the
advantage of being I/O efficient. For an overview of this approach, see
- <link xlink:href="http://www.cloudera.com/content/cloudera/en/resources/library/hbasecon/video-hbasecon-2012-lessons-learned-from-opentsdb.html">Lessons Learned from OpenTSDB</link>
- from HBaseCon2012.
+ <xref linkend="schema.casestudies.log-timeseries.log-steroids"/>.
</para>
</section>
</section>
+ <!-- note: the following id is not consistent with the others becaus it was formerly in the Case Studies chapter,
+ but I didn't want to break backward compatibility of the link. But future entries should look like the above case-study
+ links (schema.casestudies. ...) -->
+ <section xml:id="casestudies.schema.listdata">
+ <title>Case Study - List Data</title>
+ <para>The following is an exchange from the user dist-list regarding a fairly common question:
+ how to handle per-user list data in Apache HBase.
+ </para>
+ <para>*** QUESTION ***</para>
+ <para>
+ We're looking at how to store a large amount of (per-user) list data in
+HBase, and we were trying to figure out what kind of access pattern made
+the most sense. One option is store the majority of the data in a key, so
+we could have something like:
+ </para>
+
+ <programlisting>
+<FixedWidthUserName><FixedWidthValueId1>:"" (no value)
+<FixedWidthUserName><FixedWidthValueId2>:"" (no value)
+<FixedWidthUserName><FixedWidthValueId3>:"" (no value)
+ </programlisting>
+
+The other option we had was to do this entirely using:
+ <programlisting>
+<FixedWidthUserName><FixedWidthPageNum0>:<FixedWidthLength><FixedIdNextPageNum><ValueId1><ValueId2><ValueId3>...
+<FixedWidthUserName><FixedWidthPageNum1>:<FixedWidthLength><FixedIdNextPageNum><ValueId1><ValueId2><ValueId3>...
+ </programlisting>
+ <para>
+where each row would contain multiple values.
+So in one case reading the first thirty values would be:
+ </para>
+ <programlisting>
+scan { STARTROW => 'FixedWidthUsername' LIMIT => 30}
+ </programlisting>
+And in the second case it would be
+ <programlisting>
+get 'FixedWidthUserName\x00\x00\x00\x00'
+ </programlisting>
+ <para>
+The general usage pattern would be to read only the first 30 values of
+these lists, with infrequent access reading deeper into the lists. Some
+users would have <= 30 total values in these lists, and some users would
+have millions (i.e. power-law distribution)
+ </para>
+ <para>
+ The single-value format seems like it would take up more space on HBase,
+but would offer some improved retrieval / pagination flexibility. Would
+there be any significant performance advantages to be able to paginate via
+gets vs paginating with scans?
+ </para>
+ <para>
+ My initial understanding was that doing a scan should be faster if our
+paging size is unknown (and caching is set appropriately), but that gets
+should be faster if we'll always need the same page size. I've ended up
+hearing different people tell me opposite things about performance. I
+assume the page sizes would be relatively consistent, so for most use cases
+we could guarantee that we only wanted one page of data in the
+fixed-page-length case. I would also assume that we would have infrequent
+updates, but may have inserts into the middle of these lists (meaning we'd
+need to update all subsequent rows).
+ </para>
+ <para>
+Thanks for help / suggestions / follow-up questions.
+ </para>
+ <para>*** ANSWER ***</para>
+ <para>
+If I understand you correctly, you're ultimately trying to store
+triples in the form "user, valueid, value", right? E.g., something
+like:
+ </para>
+ <programlisting>
+"user123, firstname, Paul",
+"user234, lastname, Smith"
+ </programlisting>
+ <para>
+(But the usernames are fixed width, and the valueids are fixed width).
+ </para>
+ <para>
+And, your access pattern is along the lines of: "for user X, list the
+next 30 values, starting with valueid Y". Is that right? And these
+values should be returned sorted by valueid?
+ </para>
+ <para>
+The tl;dr version is that you should probably go with one row per
+user+value, and not build a complicated intra-row pagination scheme on
+your own unless you're really sure it is needed.
+ </para>
+ <para>
+Your two options mirror a common question people have when designing
+HBase schemas: should I go "tall" or "wide"? Your first schema is
+"tall": each row represents one value for one user, and so there are
+many rows in the table for each user; the row key is user + valueid,
+and there would be (presumably) a single column qualifier that means
+"the value". This is great if you want to scan over rows in sorted
+order by row key (thus my question above, about whether these ids are
+sorted correctly). You can start a scan at any user+valueid, read the
+next 30, and be done. What you're giving up is the ability to have
+transactional guarantees around all the rows for one user, but it
+doesn't sound like you need that. Doing it this way is generally
+recommended (see
+here <link xlink:href="http://hbase.apache.org/book.html#schema.smackdown">http://hbase.apache.org/book.html#schema.smackdown</link>).
+ </para>
+ <para>
+Your second option is "wide": you store a bunch of values in one row,
+using different qualifiers (where the qualifier is the valueid). The
+simple way to do that would be to just store ALL values for one user
+in a single row. I'm guessing you jumped to the "paginated" version
+because you're assuming that storing millions of columns in a single
+row would be bad for performance, which may or may not be true; as
+long as you're not trying to do too much in a single request, or do
+things like scanning over and returning all of the cells in the row,
+it shouldn't be fundamentally worse. The client has methods that allow
+you to get specific slices of columns.
+ </para>
+ <para>
+Note that neither case fundamentally uses more disk space than the
+other; you're just "shifting" part of the identifying information for
+a value either to the left (into the row key, in option one) or to the
+right (into the column qualifiers in option 2). Under the covers,
+every key/value still stores the whole row key, and column family
+name. (If this is a bit confusing, take an hour and watch Lars
+George's excellent video about understanding HBase schema design:
+<link xlink:href="http://www.youtube.com/watch?v=_HLoH_PgrLk)">http://www.youtube.com/watch?v=_HLoH_PgrLk)</link>.
+ </para>
+ <para>
+A manually paginated version has lots more complexities, as you note,
+like having to keep track of how many things are in each page,
+re-shuffling if new values are inserted, etc. That seems significantly
+more complex. It might have some slight speed advantages (or
+disadvantages!) at extremely high throughput, and the only way to
+really know that would be to try it out. If you don't have time to
+build it both ways and compare, my advice would be to start with the
+simplest option (one row per user+value). Start simple and iterate! :)
+ </para>
+ </section> <!-- listdata -->
</section> <!-- schema design cases -->
<section xml:id="schema.ops"><title>Operational and Performance Configuration Options</title>
@@ -652,4 +792,3 @@ reasonable spread in the keyspace, simil
</section>
</chapter> <!-- schema design -->
-