By Michael Rosenblum, Lewis Cunningham, Arup Nanda
Expert PL/SQL Practices is a ebook of amassed knowledge on PL/SQL programming from the very best and the brightest within the box. every one bankruptcy is a deep-dive right into a particular challenge, expertise, or characteristic set that you’ll face as a PL/SQL programmer. each one writer has selected their subject out of the powerful trust that what they percentage could make a favorable distinction within the caliber and scalability of code that you simply write.
The route to mastery starts with syntax and the mechanics of writing statements to make issues take place. If you’ve reached that time with PL/SQL, then enable the authors of Expert PL/SQL Practices make it easier to mix syntax and mechanics with positive factors and methods to actually make the language sing. You’ll discover ways to do extra with much less attempt, to put in writing code that scales and plays good, and to dispose of and keep away from defects.
These authors are obsessed with PL/SQL and the facility it areas at your disposal. they need you to be triumphant, to grasp all that PL/SQL can supply. enable Expert PL/SQL Practices open your eyes to the entire strength of Oracle’s world-class language for the database engine.
- Goes past the handbook to hide stable recommendations and top practices
- Delivers wisdom frequently received in simple terms by means of tough adventure
- Covers the performance that distinguishes PL/SQL as a robust and scalable programming language for deploying common sense contained in the database engine
Read Online or Download Expert PL/SQL Practices: for Oracle Developers and DBAs PDF
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Extra resources for Expert PL/SQL Practices: for Oracle Developers and DBAs
MDAHLS ,AW DESIGNED TO PREDICT THE SPEEDUP OF FIXED PROBLEMS SIZES AND SERIAL PORTIONS RANGING FROM TO SIMPLY DOESNT PROVIDE A FRAMEWORK FOR DEALING WITH PROBLEM SIZES THIS LARGE THAT ARE GROWING AT THIS NEW RATE 4EN TO TWENTY TIMES SPEEDUPS JUST ARENT ENOUGH WE NEED TO LOOK BEYOND SERIAL SPEEDUP AT WAYS TO HANDLE LARGER AND LARGER DATA SETS 'USTAFSONS ,AW WHICH INCLUDES THE IDEA THAT PEOPLE WOULD LIKE SOLVE EVER LARGER PROBLEMS WITHIN A RELATIVELY FIXED TIME COUPLED WITH THE DECLINE IN PROCESSOR FREQUENCY SPEEDUPS IN HAS LED TO THE RENEWED INTEREST IN PARALLEL PROGRAMMING 0ARALLEL VS $ISTRIBUTED 0ROCESSING ! T THIS POINT YOU MAY BE WONDERING ABOUT HOW TO ACHIEVE PARALLEL PROCESSING IN A DATABASE ENVIRONMENT 9OU MAY HAVE HAD EXPOSURE TO SOME OF THE NEWER DATA PROCESSING FRAMEWORKS THAT USE MANY INEXPENSIVE INDIVIDUAL COMPUTERS NETWORKED TOGETHER TO PERFORM DATA ANALYSIS TASKS IN A WAY THAT SOUNDS LIKE PARALLEL PROCESSING ! FTER ALL OUR EXAMPLES FROM NATURE SEEM LIKE PERFECT MATCHES FOR THIS KIND OF ARCHITECTURE 4HESE KINDS OF ENVIRONMENTS ARE USUALLY CLASSIFIED AS DISTRIBUTED COMPUTING ENVIRONMENTS WHICH ARE DISTINGUISHED BY A LACK OF ACCESS TO A SHARED MEMORY AREA AND CONSEQUENTLY THE NEED TO COMMUNICATE VIA MESSAGE PASSING OVER SOME KIND OF NETWORK )N A DISTRIBUTED ENVIRONMENT THERE IS SIGNIFICANT OVERHEAD DUE TO THE NEED FOR SYSTEMS TO COORDINATE THEIR ACTIVITIES OVER THIS SLOW COMPARED TO LOCAL PROCESSING SPEED NETWORK ! LSO IN DISTRIBUTED SYSTEMS ITS ASSUMED THAT EACH PROCESS CAN ONLY SEE A PORTION OF THE DATANONE OF THE PROCESSES HAS ACCESS TO THE ENTIRE DATA SET 4HIS LIMITS THE APPLICABILITY OF DISTRIBUTED ALGORITHMS 4HEY WORK WELL WHEN THE DATA IS ALREADY DISTRIBUTED AMONG THE NODES OR IF THE DATA SET IS SO LARGE THAT THE OVERHEAD TASKS OF SPLITTING AND DISTRIBUTING THE DATA INCLUDING THE INTER
NODE COMMUNICATION OVERHEAD ARE MINUSCULE WHEN COMPARED TO THE OVERALL DATA SET SIZE %VEN SO THERE IS SIGNIFICANT OVERLAP BETWEEN PARALLEL AND DISTRIBUTED PROCESSING ! PARALLEL SYSTEM MAY BE DESCRIBED AS A TIGHTLY COUPLED DISTRIBUTED SYSTEM WHILE A DISTRIBUTED SYSTEM MAY BE DESCRIBED AS A LOOSELY COUPLED PARALLEL SYSTEM 4HE GOOD NEWS IS THAT MOST DISTRIBUTED ALGORITHMS ARE EASILY TRANSLATED TO PARALLEL PROCEDURES SO IF YOU COME ACROSS A DISTRIBUTED PROCEDURE THAT SOUNDS PROMISING YOU SHOULD BE ABLE TO MODIFY IT TO RUN ON A PARALLEL ARCHITECTURE 0ARALLEL (ARDWARE ! RCHITECTURES 4HERE ARE SEVERAL KINDS OF HARDWARE ARCHITECTURES THAT MAY BE SUITABLE FOR PARALLEL PROCESSING )TS ALSO USEFUL TO UNDERSTAND WHICH ARCHITECTURAL FEATURES MAKE A SYSTEM LESS SUITABLE FOR THE REQUIREMENTS OF A PARALLEL PROCEDURE #(! 04%2 ■ 0,31, !. $ 0! 2! ,,%, 02/#%33). ' v 3INGLE COMPUTER SINGLE PROCESSOR SINGLE CORE ! S A BASE CASE THIS KIND OF COMPUTER IS RARELY ENCOUNTERED BUT ITS USEFUL TO NOTE THAT A SINGLE CORE SINGLE PROCESSOR ISOLATED COMPUTER CAN ONLY DO ONE THING AT A TIME 4HERE IS NO WAY TO IMPLEMENT A PARALLEL PROCEDURE ON SUCH A SYSTEM v 3INGLE COMPUTER SINGLE PROCESSOR MULTI
CORE )F THE SYSTEM EXPOSES THE MULTIPLE CORES AS SEPARATE PROCESSORS TO THE OPERATING SYSTEM THEN ITS POSSIBLE TO EXPLOIT THOSE CORES IN PARALLEL 'ENERALLY THESE CORES SHARE ACCESS TO A HIGH
SPEED MEMORY CACHE ON THE CHIP AND THEREFORE CAN EASILY SHARE COORDINATION INFORMATION v 3INGLE COMPUTER MULTI
PROCESSOR SINGLE OR MULTI
CORE /FTEN CALLED SYMMETRIC MULTIPROCESSING SYSTEMS 3-0 THESE KINDS OF COMPUTERS HAVE BEEN THE MAINSTAY OF OPEN SYSTEMS 4HESE SYSTEMS HAVE PROCESSORS THAT MAY NOT SHARE A LOCAL HIGH SPEED MEMORY BUT ALL OF THEM SHARE ACCESS TO THE MAIN COMPUTER MEMORY THROUGH A MEMORY BUS 4HIS SHARED MEMORY ACCESS ENABLES THE PROCESSORS TO COORDINATE THEIR ACTIVITIES )N SOME OF THESE SYSTEMS THE PROCESSORS ARE GROUPED TOGETHER ON PROCESSOR BOARDS INCLUDING A LARGE AMOUNT OF MEMORY )F THAT MEMORY IS SHARED ACROSS PROCESSOR BOARDS SUCH ACCESS MAY BE NON
UNIFORM RESULTING IN UNEVEN MEMORY ACCESS TIMES v #LUSTERED SYSTEMS OF 3-0 COMPUTERS #LUSTERED SYSTEMS USUALLY EMPLOY SOME KIND OF HIGH
SPEED DEDICATED SYSTEM INTERCONNECTION NETWORK TO FACILITATE COMMUNICATION BETWEEN THE COMPUTER NODES 4HESE KINDS OF COMPUTER CLUSTERS MAY OR MAY NOT SHARE ACCESS TO DISKS 7HEN THEY SHARE ACCESS TO DISKS THEY ARE CALLED SHARED EVERYTHING ARCHITECTURES 7HEN THEY DONT THEY ARE CALLED SHARED NOTHING ARCHITECTURES AND MORE CLOSELY RESEMBLE DISTRIBUTED SYSTEMS )N SOME VARIANTS OF CLUSTERS THE HIGH
SPEED INTERCONNECT ACTUALLY ENABLES REMOTE ACCESS TO THE MEMORY OF EACH INDIVIDUAL COMPUTER NODE FROM ALL OTHER NODES 7HILE SUCH REMOTE MEMORY ACCESS IS MUCH SLOWER THAN LOCAL MEMORY ACCESS IT IS MUCH FASTER THAN USING THE DISK SUBSYSTEM TO TRANSFER INFORMATION BETWEEN NODES /RACLE 2EAL !