1. Unit 06 : Index and Distributed Caching
COMP 5323
Web Database Technologies and Applications 2014

2. Doctrine of Fair Use
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3. Learning Objectives
Understand different path index techniques to improve the performance.
Learn a distributed memory caching system which improves the performance of web database applications

4. Outline
Index for Semi-structured data
Distributed Caching

5. 1 Index for Semi-structured Data

6. Why is Indexing Needed?
Allows fast access to data by replicating portions of the data in special purpose structures.
Despite the additional cost (storage, maintenance and complexity) they have shown to be useful in evaluating queries.

7. Index Types Structural index Content index
Accessing all elements of given name
Ancestor-descendant and parent-child relationship between elements
Content index
Accessing elements containing given keywords
Supporting most text search functionalities

8. Classical Content Index
Classically based on inverted lists
For each term, gives the doc.ID + localization
Several variations allows different search types
Offset, Relative, Proximity
Generally stored in a B+-Tree to optimize search for a given word
Size is an important issue
Memory and Disk
Words Localization
- t1 : doc1-100, doc1-300, doc3-200, …
- t2 : doc2-30, doc4-70, …
- t3 : doc4-87, doc5-754, …
(word, localization)
Fixed entry (word repeated)
(word, Frequency, (localization)*)
Variable length entry
Short Reference:

9. Problem with XML Query processing Support of updates
Support of element addressing
Doc.ID should include NodeId (Xpath) + Offset
Index size becomes very large
XPath are long
Support of typed data
Integer, float, simple types of XML schema
Requires classical indexes for certain elements
Query processing
Structural joins
Text search
Exact search
Support of updates
Incremental updates would be a plus

10. Path-based approach
Represent XML document into tree or graph structure
Index XML document directly
Without the support of DTD
Mainly use the memory as the index storage
Properties
Keep the structural information to improve query performance
Easy to support query with regular path expression

11. Different Approaches Patricia Trie Cooper et al. 2001 DataGuides
J. McHugh et al., 1997
T-Index
Tova Milo and Dan Sucin
APEX (Adaptive Path Index for XML Data)
C. W. Chung et al., 2002
Dewey Structure
K-ary Table
Path Table
OrdPath

12. Partricia Tries
A compact representation of a trie in which any node that is an only child is merged with its parent.
Also known as radix tree

13. Partricia Tries Cooper et al. 2001 Idea:
Partitioned Partricia Tries to index strings
Encode XPath expressions as strings (encode names, encode atomic values)
<book>
<author>Whoever</author>
<author>Not me</author>
<title>No Kidding</title>
</book>
B A 1 Whoever
B A 2 Not me
B T No Kidding

14. DataGuides
World-Wide Web demonstrates that much of the information available online is semistructured.
Graph-based data model called OEM, for Object Exchange Model

15. A sample OEM database

16. Lore Language (Lorel Query)
Select Restaurant.Entree
returns all entrees served by any restaurant, the set of objects {6, 10, 11}
Select Restaurant.Name
where Restaurant.Entree = “Burger”
The answer to the query is the single object 5.

17. DataGuide

18. T-index

19. 1-Index
1-Index DataGuides

20. 2-Index

21. APEX

22. Representation of XML Data Structure

23. DataGuide

24. APEX
HAPEX GAPEX

25. Dewey - Structure
Each node is assigned a label that represents the path from the document’s root to the node.
Each component of the label represents the local order of an ancestor node.
Nodes with the same number of delimiters (“.”) in their label are in the same level.
Bib
book
paper
author
Tim
Sarah
(0)
(0.0)
(0.0.0)
( )
(0.1)
(0.2)
(0.2.0)
( )

26. Dewey – Supported Queries (1/3)
Ancestors / Descendants
Node “X” is an ancestor of node “Y” if the label of node “X” is a substring of the label of node “Y”.
Bib
book
paper
author
Tim
Sarah
(0)
(0.0)
(0.0.0)
( )
(0.1)
(0.2)
(0.2.0)
( )

27. Dewey – Supported Queries (2/3)
Parent / Child
Node “X” is parent of node “Y” if:
- The label of node “X” is a substring of the label of node “Y”
- And frags(X) = frags(Y) – 1, where frags(X) is the number of delimiters of the label of node X and frags(Y) is the number of delimiters of label of node Y.
Bib
book
paper
author
Tim
Sarah
(0)
(0.0)
(0.0.0)
( )
(0.1)
(0.2)
(0.2.0)
( )

28. Dewey – Supported Queries (3/3)
Siblings
Nodes “X” and “Y” are siblings if:
- They have the same number of delimiters in their labels
- And X.prefix = Y.prefix, where prefix is the label of the node without its positional identifier
Bib
book
paper
author
Tim
Sarah
(0)
(0.0)
(0.0.0)
( )
(0.1)
(0.2)
(0.2.0)
( )

29. Dewey – Updates Insertion of new node
The label of the nodes in the subtree rooted at the following sibling need to be updated
O(n) nodes need relabeling, where n is the number of nodes of the XML file
(0)
Bib
(0.3)
(0.0)
(0.2)
book
paper
(0.3.0)
(0.2.0)
(0.0.0)
paper
paper
(0.2)
author
(0.1)
author
( )
( )
( )
Tim
Sarah

30. Dewey Not efficient for dynamic XML files with many updates
Need to re-label many nodes
As the depth of the tree increases:
Label size of a node increases rapidly
Storage size increases rapidly
It becomes more costly to infer the supported queries between any two nodes (the string prefix matching becomes longer)
Overflow problem
The original fixed length of bits assigned to store the size of the label is not enough.

31. Document Tree Lee et al, ACM DL 1996.
Represent each document as a k-ary complete tree and assign a UID to each node a
3-ary tree c d e f g h i j
real node
virtual node e

32. K-ary table
Each document is assigned k, which is the maximum number of siblings in the document tree.
Each element has an entry (row) in the K-ary table
When a query is issued, the result set has pointers to the K-ary table.

33. Level and Element Type Number
Level means the level in the document tree
It gives a clue how many parent function is applied to get to a target element
Element type number
A unique number is assigned to each element type in DTD It enables to filter out unnecessary elements and accumulate the correct frequencies
Element location
The unique position of an element instance in a document tree

34. Element Labeling Document (1) Chapter (4) Title (2) Abstract (3)
Section
(6)
Para
(5)
Para
(7)

35. Result of assigning UIDs
Unique element identifier
parent(i) = [(i-2)/k+1] d
3-ary tree c s p e
Result of assigning UIDs

36. XML Index Path Table (Oracle)
Some Typos
XML Index Path Table (Oracle)
<po> <data> <item>foo</item> <pkg>123</pkg> <item>bar</item> </data>
</po>
BaseRid
Path
OrderKey
Value
Locator
NumValue
Rid1 po
po.data 1 11
po.data.item
1.1
“foo” 17
po.data.pkg
1.2
“123” 32
123
1.3
“bar” 46

37. OrdPath ORDPATHs: Insert-Friendly XML Node Labels
Patrick O’Neil, Elizabeth O’Neil1, Shankar Pal, Istvan Cseri, Gideon Schaller, Nigel Westbury
SIGMOD 2004
SQL Server 2005 implementation

38. OrdPath
Aims to provide efficient insertion at any position of an XML tree, and also supports extremely high performance query plans for native XML queries.
Tree modifications
new may be inserted
sub-trees be deleted
sub-trees may be moved around within the tree

39. OrdPath
Encodes the parent-child relationship by extending the parent’s ORDPATH label with a component for the child.
E.g.: might be the parent ORDPATH, the child.
The various child components reflect the children’s relative sibling order, so that byte-by-byte comparison of the ORDPATH labels of two nodes yields the proper document order.
A new node (possibly a root node of a sub-tree) can be inserted under any designated parent node in an existing tree.
Its label is generated using an additional intermediate “careting” component that falls between the components of its left and right siblings.

40. OrdPath At the beginning Inserting in the middle
Only positive, odd integers are assigned during an initial load; even-numbered and negative integer component values are reserved for later insertions into an existing tree
Inserting in the middle
Even numbers are used as carets only. Do not count as components that increase the depth of the nodes.
E.g. new nodes in between and 3.5.7
New siblings: , , …
A subtree: , , , , , , , , ,

41. XML

42. ORDPATH Label of Nodes BOOK 1 Section 1.5 @ISBN 1.1 Section 1.3
tree frogs
1.5.7
Title
1.5.1
Figure
1.5.5
Nobody…
1.3.3
Title
1.3.1
Figure
1.3.5
All right…
1.5.3
CAPTION

43. Infoset Table

44. 2 Memcached

45. What is memcached briefly?
memcached is a high-performance, distributed memory object caching system, generic in nature
It is a key-based cache daemon that stores data and objects wherever dedicated or spare RAM is available for very quick access
It is a dumb distributed hash table. It does not provide redundancy, failover or authentication. If needed the client has to handle that.

46. Why was memcached made?
It was originally developed by Danga Interactive to enhance the speed of LiveJournal.com
It dropped the database load to almost nothing, yielding faster page load times for users, better resource utilization, and faster access to the databases on a memcache miss

47. Memcached

48. Where does memcached reside?
Memcache is not part of the database but sits outside it on the server(s).
Over a pool of servers

49. Architecture

50. When should I use memcached?
When your database is optimized to the hilt and you still need more out of it.
Lots of SELECTs are using resources that could be better used elsewhere in the DB.
Locking issues keep coming up
When table listings in the query cache are torn down so often it becomes useless
To get maximum “scale out” of minimum hardware

51. Hit-rate Management
anything what is more expensive to fetch from elsewhere, and has sufficient hitrate, can be placed in memcached
How often will object or data be used?
How expensive is it to generate the data?
What is the expected hitrate?
Will the application invalidate the data itself, or will TTL be used?
How much development work has to be done to embed it?
TTL - time to live

52. Why use memcached?
To reduce the load on the database by caching data BEFORE it hits the database
Can be used for more then just holding database results (objects) and improve the entire application response time
Feel the need for speed
Memcache is in RAM - much faster then hitting the disk or the database

53. Why not use memcached?
Memcache is held in RAM. This is a finite resource.
Adding complexity to a system just for complexities sake is a waste. If the system can respond within the requirements without it - leave it alone

54. What are the limits of memcached?
Keys can be no more then 250 characters
Stored data can not exceed 1M (largest typical slab size)
There are generally no limits to the number of nodes running memcache
There are generally no limits the the amount of RAM used by memcache over all nodes
32 bit machines do have a limit of 4GB though

55. Platform
You can build and install memcached from the source code directly, or you can use an existing operating system package or installation.
on a RedHat, Fedora or CentOS host, use yum:
root-shell> yum install memcached
on a Debian or Ubuntu host, use apt-get:
root-shell> apt-get install memcached
on a Gentoo host, use emerge:
root-shell> emerge install memcached
on OpenSolaris, use the pkg for SUNWmemcached:
root-shell> pkg install SUNWmemcached

56. Port 11211
Get the source from the website:
Memcache has a dependancy on libevent so make sure you have that also.
Decompress, cd into the dir
./configure;make;make install;
Memcached listens on port by default, this can be changed with –p option.

57. How do I start memcached?
Memcached can be run as a non-root user if it will not be on a restricted port (<1024) - though the user can not have a memory limit restriction
shell> memcached
Default configuration - Memory: 64MB, all network interfaces, port:11211, max simultaneous connections: 1024

58. Memcached options
You can change the default configuration with various options.
-u <user> : run as user if started as root
-m <num> : maximum <num> MB memory to use for items
If more then available RAM - will use swap
Don’t forget 4G limit on 32 bit machines
-d : Run as a daemon
-l <ip_addr> : Listen on <ip_addr>; default to INDRR_ANY
-p <num> : port

59. How can I connect to memcached?
Memcached uses a protocol that many languages implement with an API.
Languages that implement it:
Perl, PHP, Python, Ruby, Java, C#, C, Lua, Postgres, MySQL, Chicken Scheme
And yes - because it is a protocol you can even use telnet
shell> telnet localhost 11211
Protocol at

60. Memcached protocol Three types of commands
Storage - ask the server to store some data identified by a key
set, add, replace, append, prepend and cas
Retrieval - ask the server to retrieve data corresponding to a set of keys
get, gets

61. Memcached protocol (con’t)
All others that don’t involve unstructured data
Deletion:delete
Statistics: stats,
flush_all: always succeeds, invalidate all existing items immediately (by default) or after the expiration specified.
version, verbosity, quit

62. PHP and Memcached Make sure you have a working Apache/PHP install
PHP has a memcached extension available through pecl.
Installation:
shell> pecl install memcache
Make sure the pear is installed (debian: apt-get install php-pear)
Make sure that you also have php5-dev installed for phpize.
shell> apt-get install php5-dev

63. PHP Script Example
Information about the PHP API at
<?php
// make a memcache object
$memcache = new Memcache;
// connect to memcache
$memcache->connect('localhost', 11211) or die ("Could not connect");
//get the memcache version
$version = $memcache->getVersion();
echo "Server's version: ".$version."<br/>\n";

64. PHP Script (con’t) // test data $tmp_object = new stdClass;
$tmp_object->str_attr = 'test';
$tmp_object->int_attr = 123;
// set the test data in memcache
$memcache->set('key', $tmp_object, false, 10) or die ("Failed to save data at the server");
echo "Store data in the cache (data will expire in 10 seconds)<br/>\n";
// get the data
$get_result = $memcache->get('key');
echo "Data from the cache:<br/>\n";
echo ‘<pre>’, var_dump($get_result), ‘</pre>’;
MEMCACHE_COMPRESSED

65. PHP Script (con’t) // modify the data
$tmp_object->str_attr = ‘boo’;
$memcache->replace(‘key’, $tmp_object, false, 10) or die(“Failed to save new data to the server<br/>\n”);
Echo “Stored data in the cache changed<br/>\n”;
// get the new data
$get_result = $memcache->get(‘key’);
Echo “New data from the cache:<br/>\n”;
Echo ‘<pre>’, var_dump($get_result), “</pre>\n”;
// delete the data
$memcache->delete(‘key’) or die(“Data not deleted<br/>\n”);

66. MySQL’s memcached The API is consistent with the other API’s
Connect: mysql> SELECT memc_servers_set(' :11211, :11211');
The list of servers used by the memcached UDFs is not persistent over restarts of the MySQL server.
Set: mysql> SELECT memc_set('myid', 'myvalue');
Retreive: mysql> SELECT memc_get('myid');
Full listing of functions are at

67. Possible ways to secure memcached
It has no authentication system - so protection is important
Run as a non-priveledged user to minimize potential damage
Specify the ip address to listen on using -l
, , specific ip address
Use a non-standard port
Use a firewall

68. Memcached

69. Memcached Memory Management
Slab Allocation: When you start to store data into the cache, memcached does not allocate the memory for the data on an item by item basis. Instead, a slab allocation is used to optimize memory usage and prevent memory fragmentation when information expires from the cache.
Lazy Expiration + LRU
Lazy Expiration: When an item is requested (a get request) Memcached checks the expiration time to see if the item is still valid before returning it to the client.
LRU (least recently used): Memcached is LRU per slab class, but not globally LRU.

70. Slab Allocation

71. Memcached Distributed Architecture
//Obtain a server ID based on Key value
int getServerId(char *key, int serverTotal) {
int c, hash = 0;
while (c = *key++) {
hash += c; }
return hash % serverTotal;
//a list of servers
node[0] => :11211
node[1] => :11211
node[2] => :11211
//get id
int id = getServerId("test", 3);
//get ip address and port number
node[id] == node[1]

72. Memcached Distributed Architecture

73. SQL Server Cache
SQL Server cache mechanism : - Query plans - pages from the database files
but it does NOT cache: - exact results from a query
REFERENCE

74. Reference
DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases
Index Structure for Path Expressions
APEX: An Adaptive Path Index for XML Data

75. Reference Only
Memcached should run on Linux. It may not work on some windows

76. Reference

77. Reference
0: <flag>
60: timeout
6: length