An Overview of a Scalable Distributed Database System: SD-SQL Server Witold LITWIN, Soror SAHRI & Thomas SCHWARZ Ceria Laboratory Comp. Eng. Dep. Paris-Dauphine University Santa Clara U. BNCOD 2006

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 2 1.Introduction 2.Architecture 3.Command Interface 4.Processing 5.Performance 6.Conclusion & Future Work Overview

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 3 Most DBSs have distributed/parallel versions with partitioned tables SQL Server, Oracle, DB2, MySQL, Postgres… Partitioned Tables

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 4 BENEFITS OF PARTITIONING Partitioning can provide tremendous benefits to a wide variety of applications by improving manageability, performance, and availability. It is not unusual for partitioning to improve the performance of certain queries or maintenance operations by an order of magnitude. Moreover, partitioning can greatly simplify common administration tasks. Partitioning also enables database designers and administrators to tackle some of the toughest problems posed by cutting-edge applications. Partitioning is a key tool for building multi-terabyte systems or systems with extremely high availability requirements. Partitioning in Oracle Database 10g Release 2 An Oracle White Paper May 2005

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 5 DBSs require manual partitioning And manual repartitioning when tables scale-up DBSs do not provide dynamically scalable tables Hassle of Partitioning

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 6   Research Report, December 2005  [Oracle Database 10g] Facts

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 7 Scalable Distributed Partitioning of Relational Tables Scalable Distributed Database System SD-DBS SD-SQL Server Goal

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 8 Several SDDS schemes are well-known by now: LH*, RP*, k-RP*, LH* RS …Chord, VBI & most of P2P schemes The domain has over references on Google An SD-DBS reuses SDDS design principles With DB management specificity A scalable distributed data structure Specifically designed for possibly very large data on multi-computers or networks of WSs P2P & Grids in modern vocabulary  Why SDDS Role Model? Role Model: an SDDS

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 9 The first and yet the only SD-DBS Implements the SD-DBS architecture Litwin, Schwartz & Risch (2002) Runs on Microsoft SQL Server 2000 Shared Nothing Architecture Up to 250 nodes at present SD-SQL Server

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 10 Linked SQL Servers D1 D2DiDi+1 SSPC D1_T _D1_T User/Application T sd_create_table User/Application sd_insert _D1_T Split NDBs SD-SQL server SD-SQL client SD-SQL Server Managers SD-SQL peer Gross Architecture

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 11 DB1 Node1Node2Node3Nodei DB1DB1 …… DB1DB1 MDB DB1 SDB DB2 SDB DB2 Nodes, SDBs & NDBs

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 12 Primary NDB  First for an SDB Client NDB Interfaces applications & users Carries only images No actual tables with application data  Server NDB Carries actual tables segments Peer NDB Both functions NDB Types

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 13 For the application: a table of an SDB Internally: a collection of segments behind client images A segment is an SQL table One per NDB of the SDB Sharing the scalable table scheme Except its check constraint Min and Max value of the partition key With size limit Splitting when overflows occur The check constraints partition the partition key space Scalable (Distributed) Table

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 14 The primary segment First allocated for a new table At some server or peer NDB of SDB The peer creating the table The primary server of the client creating the table Scalable (Distributed) Table

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 15 Linked SQL Servers D1 D2DiDi+1 SSPC D1_T _D1_T User/Application T sd_create_table User/Application sd_insert _D1_T Split NDBs SD-SQL server SD-SQL client SD-SQL Server Managers SD-SQL peer Gross Architecture

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 16 For the application, it the client image is the table The image name is the table name Primary image Created during the scalable table creation at the client or peer NDB creating the table Secondary images Created later on On other NDBs of the SDB For local applications By a dedicated command sd_Create Image…. Scalable (Distributed) Table

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 17 Internally, every image is a specific SQL Server view of the segments: Distributed partitioned union view CREATE VIEW T AS SELECT * FROM N2.DB1.SD._N1_T UNION ALL SELECT * FROM N3.DB1.SD._N1_T UNION ALL SELECT * FROM N4.DB1.SD._N1_T Updatable Through the check constraints With or without Lazy Schema Validation Scalable (Distributed) Table

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 18 Linked SQL Servers D1 D2DiDi+1 SSPC D1_T _D1_T User/Application T sd_create_table User/Application sd_insert _D1_T Split NDBs SD-SQL server SD-SQL client SD-SQL Server Managers SD-SQL peer Gross Architecture

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 19 Store various SD-SQL Server meta-data In particular about each scalable table At each server or peer NDB SD.Size meta-table Segment capacity The number of stored tuples triggering a split Same for every segment at present SD.RP meta-table the actual partitioning of the scalable table The location of each segment SD.Primary table The location of the SD.RP table for each segment in the NDB SD SQL Server Meta-Tables

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 20 At every client or peer NDB In SD.Image table All the local images The name of the image The type Primary or secondary The number of segments As seen by an image Not necessarily the actual one SD SQL Server Meta-Tables

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 21 At every NDB SD.SDBNode points towards the primary NDB SD.MDBNode points towards the MDB At MDB SD.Nodes indicates all the available SD-SQL Server nodes Over linked SQL Server nodes SD.SDB describes all the SDBs At every primary NDB SD.NDB points to every NDB of the SDB SD SQL Server Meta-Tables

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 22 ……. DB1 SDB N1.DB1N2.DB1N3.DB1 T Scalable Table Ni.DB Size N1.DB1 Primary Ni.DB1 Nodes N1.DB1 N2.DB1 N3.DB1 RP Meta-Tables Scalable Tables: Meta-data SDBNode

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 23 The number of segments in a scalable table may grow An overflowing segment splits Creating one or more new segments A split occurs when an insert overflows the segment capacity The trigger launches the split as an asynchronous job called splitter To avoid the application level timeout Scalable Table Expansion

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 24 Linked SQL Servers D1 D2DiDi+1 SSPC D1_T _D1_T User/Application T sd_create_table User/Application sd_insert _D1_T Split NDBs SD-SQL server SD-SQL client SD-SQL Server Managers SD-SQL peer Gross Architecture

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 25 Every new segment Is basically created at an existing NDB that does not yet have any segments of the expanding table provided there is any Otherwise a new NDB is first appended to SDB Provided there is an available SD SQL Server node Inherits the “father”’s schema Gets its new check constraint Gets indexes as defined at the “father” Scalable Table Expansion

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 26 S b+1 S S1S1 p b+1-p p=INT(b/2) C( S)=   { c: c < h = c (b+1-p)} C( S 1 )={c: c > = c (b+1-p)} Check Constraint? b SELECT TOP Pi * INTO Ni.Si FROM S ORDER BY C ASC SELECT TOP Pi * WITH TIES INTO Ni.S1 FROM S ORDER BY C ASC Single Segment Split Single Tuple Insert

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 27 Single Segment Split Bulk Insert Single segment split

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 28 Multi-Segment Split Bulk Insert Multi-segment split

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 29 SDB DB1 Scalable Table T sd_insert N1N2N4N3 NDB DB1 sd_insert NDB DB1 Ni sd_create_node sd_insert N3 NDB DB1 sd_create_node_database NDB DB1 ……. sd_create_node_database SDB DB1 Split with SDB Expansion

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 30 Images An Image hides the scalable table partitioning An image is an SQL Server distributed updateable partitioned view of the table An SQL Server Union-all view with check constraints An image resides on client or peer NDBs All meta-data of an image are stored in the Image meta-table

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 31 Image Types Primary image Resides at the creation node Has the name of the scalable table Secondary images Reside at other client or peer NDBs of the SDB Have a specific name, other than that of the table  To avoid name conflict

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 32 Image Adjustment The splits do not modify synchronously the images Any split makes every image outdated The client or peer verifies every image dynamically when a query to the image comes in Image checking Image adjustment if necessary

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 33 Get the number of segments presented in the image, N1 Get the number of segments of the scalable table, N2 Compare N1 and N2: If N1<N2 then Image Adjustment Alter the partitioned view definition Image Adjustment

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 34 Image: Example N1.DB1 N2.DB1 N3.DB1 T Scalable Table CREATE VIEW T AS SELECT * FROM N2.DB1.SD._N1_TCREATE VIEW T AS SELECT * FROM N2.DB1.SD._N1_T UNION ALL SELECT * FROM N3.DB1.SD._N1_T UNION ALL SELECT * FROM N4.DB1.SD._N1_T Primary Image DB1 SDB N4.DB1 T Image

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 35  The application interface manipulates scalable tables through SD-SQL Server commands  The SD-SQL Server commands start with ‘sd_’ to distinguish from SQL Server commands for static tables INSERT sd_insert CREATE TABLE sd_create_table Application Interface

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 36 Node Creation sd_create_node ‘Dell1’ /* Server by default */ sd_create_node ‘Ceria’, ‘client’ Node Alteration sd_alter_node ‘Ceria’, ‘ADD server’ /* Becomes peer*/ Node Removal sd_drop_node ‘Ceria’ Nodes Management

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 37 SDB Creation sd_create_scalable_database ‘SkyServer’, ‘Dell1’, ‘Server’, 2 /* Creates the primary SkyServer NDB as well at Dell1*/ SDB Alteration sd_create_node_database ‘SkyServer’, ‘Ceria’, ‘Client’ SDB Removal sd_drop_scalable_database ‘SkyServer’ SDB & NDB Management

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 38 Scalable Table Creation sd_create_table ‘PhotoObj (objid BIGINT PRIMARY KEY…)’, No foreign keys yet Scalable Table Alteration sd_alter_table ‘PhotoObj ADD t INT’, 1000 sd_create_index ‘run_index ON Photoobj (run)’ sd_drop_index ‘PhotoObj.run_index’ Scalable Table Removal sd_drop_table ‘PhotoObj’ Scalable Tables Management

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 39 Secondary Image Creation sd_create_image ‘Ceria’, ‘PhotoObj’ sd_create_image ‘Dell2’, ‘PhotoObj’ Secondary Image Removal sd_drop_image 'PhotoObj’ Image Adjustment

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 40 A view of an image Involving perhaps static tables And perhaps static views … Declared under SD-SQL Server by the SQL Server CREATE VIEW command Scalable View

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 41 USE SkyServer /* SQL Server command */ Scalable Update Queries sd_insert ‘INTO PhotoObj SELECT * FROM Ceria5.Skyserver-S.PhotoObj’ Scalable Search Queries sd_select ‘* FROM PhotoObj’ sd_select ‘TOP 5000 * INTO PhotoObj1 FROM PhotoObj’, 500 Scalable Queries Management

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 42 Image Binding Let Q a scalable query using the PhotoObj image: sd_select ‘COUNT (*) FROM PhotoObj’ Find Images in Q Check PhotoObj Image for Correctness Adjust PhotoObj Image if needed Send Q’ to SQL Server for Execution Command Processing

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 43 Concurrency  SD-SQL Server processes every command as SQL distributed transaction at Repeatable Read isolation level  Tuple level locks  Shared locks  Exclusive 2PL locks  Much less blocking than the Serializable Level

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 44  Splits use exclusive locks on segments and tuples in RP meta-table.  Shared locks on other meta-tables: Primary, NDB meta-tables  Scalable queries use basically shared locks on meta-tables and any other table involved  All the conccurent executions can be shown serializable Concurrency

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 45 Splitter sd_alter_table Dell1.SkyServer Dell1 Dell2 Dell3 RP PhotoObj Exclusive Lock Waiting Exclusive Lock Shared Lock Exclusive Lock X X Concurrency: Example

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 46 Experimental Environment  6 Machines Pentium IV 1.7 GHz  RAM: 780 Mb & 1 Gb  Operating System: Windows 2K Server  Ethernet Network: max bandwidth of 1 Gb/s  Use of SQL Analyzer for editing queries  Use of SQL Profiler to take measurements

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 47 The SkyServer Benchmark We use SkyServer database as benchmark Provided and installed at Ceria by Dr. Gray SkyServer brings the entire database of the Sloan Digital Sky Survey, SDSS We use of the PhotoObj table as an example scalable table In our experiments, PhotoObj has almost 159 K tuples (about 260 MB) Originally, it has 14 M tuples

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 48 Splitting PhotoObj with 160 k tuples into 2…5 segments, according to segment capacity Split Time

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 49 Split Time Splitting PhotoObj with 160 k tuples and indexes into 2… 5 segments according to segment capacity

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 50 Split Time Analysis Longer split time may timeout a query put on wait Future solution: Incremental Splitting The splitter moves tuples by an increment at a time Let us say 1000 tuples Then ends up by calling upon itself The query may proceed as the splitter releases the exclusive lock on the RP tuple The process continues for next increment etc as long as there are tuples to move

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 51 (Q) sd_select ‘COUNT (*) FROM PhotoObj’ Query (Q1) execution time Image Adjustment

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 52 Scalable View Processing (Q) sd_select ‘COUNT (*) FROM Ti’

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 53  (Q): sd_select ‘COUNT (*) FROM PhotoObj’ Execution time of (Q) on SQL Server and SD-SQL Server SD-SQL Server / SQL Server

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 54 Scalable tables are now a reality with SD-SQL Server No more manual repartitioning Unlike in any other DBS we know about Performance analysis proves Efficiency of our design Immediate utility of SD-SQL Server Conclusion

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 55 SQL Server 2005 portage Incremental splits Virtual repository of eGov documents SQL Server XML View Foreign keys for scalable tables More performance measurements Skyserver & other benchmarks Error processing High availability Parity segments Application to other DBMSs Oracle, DB2, etc. Future Works

BNCOD 2006 – July 18 th, 2006An Overview of a Scalable Distributed Database System: SD-SQL Server 56 Thank you for your attention W ork performed between Partly founded by MsResearch EEC Icons Project EEC E-Gov Project