 SASInstitute A00-201 : SAS Base Programming ExamExam Dumps Organized by Cuthbert
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Exam Number : A00-201
Exam Name : SAS Base Programming
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A00-201 exam Format | A00-201 Course Contents | A00-201 Course Outline | A00-201 exam Syllabus | A00-201 exam Objectives
SAS Certified Specialist: Base Programming Using SAS 9.4
Read and create data files.
Manipulate and transform data.
Create basic detail and summary reports using Base SAS procedures.
Identify and correct syntax and programming logic errors.
Access and Create Data Structures
Create Temporary and permanent SAS Data sets.
Investigate SAS data libraries using base SAS utility procedures.
Access data.
Combine SAS data sets.
Create and manipulate SAS date values.
Control which observations and variables in a SAS data set are processed and output.
Manage Data
Sort observations in a SAS data set.
Conditionally execute SAS statements.
Use assignment statements in the DATA step.
Modify variable attributes using options and statements in the DATA step.
Accumulate sub-totals and totals using DATA step statements.
Use SAS functions to manipulate character data, numeric data, and SAS date values.
Use SAS functions to convert character data to numeric and vice versa.
Process data using DO LOOPS.
Restructure SAS data sets with PROC TRANSPOSE.
Use macro variables to simplify program maintenance.
Error Handling
Identify and resolve programming logic errors.
Recognize and correct syntax errors.
Generate Reports and Output
Generate list reports using the PRINT procedure.
Generate summary reports and frequency tables using base SAS procedures.
Enhance reports with user-defined formats, titles, footnotes and SAS System reporting options.
Generate reports using ODS statements.
Export data.
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SASInstitute Programming techniques
Tuning assistance for applications That Use SAS/SHARE application : computer materials Used through a Server
The counsel in this paper so far has been about SAS files and how they are used by way of an utility. You could be a greater useful application developer if, in addition to realizing a way to make most efficient use of SAS data, you also take into account the computer substances that a server consumes. That understanding will help you design your applications to make most fulfilling use of a server as well as premier use of SAS info.
A server is an independently operating SAS session that brokers requests for statistics from different SAS periods. There are four kinds of laptop substances that a server consumes:
CPU (the desktop's processor)
I/O (input from and output to the computing device's permanent storage)
memory (the desktop's working storage)
Messages (passing facts between a server and its clients)
CPU, I/O, and memory substances are consumed via each SAS session. Messages is a reputation for one measurable aspect of the complicated enviornment of communications substances; communications components are consumed via SAS/SHARE utility and SAS/connect utility as a result of these two products enable SAS classes to communicate with one one other.
Any work finished by using a server consumes multiple form of resource (if you are seeking for primary easy truths, you may additionally are looking to pass this section). A server can do several sorts of work and, as you may expect, not all types of labor eat elements in the equal relative amounts. for example, some work a server can do consumes lots of the CPU aid but little of the different elements, whereas other work consumes an awful lot of the reminiscence aid, less of the CPU useful resource, and intensely little of the other materials.
A server creates methods as users connect to it and execute statistics steps, techniques, and home windows. These approaches (created on clients' behalf) are assigned the work it truly is definitely performed in the server's SAS session. This makes it possible for a process in a server's session to do work requested by using one consumer and then yield control in order that one more process can do work for one more user.
Most requests dealt with via the approaches in a server require small bursts of CPU time. but there are a few requests that may eat exceptionally giant quantities of CPU time:
Processing a where clause
decoding a SAS facts view
Processing a compressed SAS information file
When a SAS facts set is accessed via a server, each the place clause used to opt for observations from that statistics set is evaluated by a method in the server's SAS session. This increases the server's overall use of the CPU useful resource to reduce its use of the messages aid. regularly, evaluation of a the place clause can also be optimized through the use of an index to find the preferred observations. but when an index is not used, or selects greater observations than satisfy the where clause, the process within the server's session must search for observations that absolutely satisfy the where clause. looking can eat a significant quantity of the CPU resource. whereas a process conducts a search, it yields periodically to enable other tactics within the server's session to do work for other clients.
A PROC SQL view can devour fairly slightly of the CPU resource. The SQL view engine might also be part of tables, it may wish to form intermediate info, and there may be a number of the place clauses in the view that require comparison. The method during which the SQL view engine executes yields periodically while a view is interpreted.
records step views and SAS/access views also devour the CPU useful resource. The procedure during which both of these engines executes doesn't yield to permit other procedures to run, however the server itself makes it possible for different strategies to run when a group of observations has been organized for transmission to a consumer's SAS session. a data step view that does a great deal of calculation while getting ready each and every remark can have a visibly dangerous have an effect on on a server's response time to different clients' requests.
When a compressed SAS facts file is read, techniques in the server's session decompress every observation; when a compressed SAS information file is created or replaced, a technique in the server's session compresses every remark. in many circumstances the time required to decompress (or compress) is shorter than the time required to study the further pages of an uncompressed file. In other phrases, trading extended use of the CPU resource for decreased use of the I/O useful resource can, on balance, in the reduction of the length of time users wait for a server to reply. whereas a person approaches a compressed records file through a server, other techniques in the server's session can also execute between agencies of observations requested through that consumer; a SAS facts file is not compressed or decompressed in its entirety in a single operation.
The "Programming ideas" section of this paper offers concepts for reducing the CPU consumption of processes in a server's session below the subject matters:
choose the appropriate subsetting approach
Index wisely
understand your software's information step views
since most work achieved by means of the processes in a server's SAS session comprises I/O undertaking, those processes can spend a big amount of time watching for I/O recreation to complete. (This time comprises relocating the pinnacle of a disk pressure to the relevant place, expecting the disk to spin around to the place of the requested information, and transferring the information from the disk to the computing device's working storage.) within the existing unencumber of SAS/SHARE application, whereas a technique in a server's session waits for I/O endeavor to finished, other approaches in the server's session do not function other work that makes use of a distinct (CPU, memory, or messages) useful resource.
That waiting may, it could look, develop into a bottleneck for a server, and in a couple of situations this issue is realized. but in apply most of a server's memory is used for I/O buffers and tactics in a server's session customarily satisfy most requests for records from I/O buffers that are already in memory.
A server typically allocates memory for one web page of a file each time the file is opened, up to the number of pages in the file. for example, if the software being performed by way of a consumer opens a file twice, ample of the server's reminiscence to comprise two pages of the file is allocated; if ten clients run the utility, area for 20 pages of the file is allocated in the server's reminiscence. The variety of buffers allotted for a file will not exceed the number of pages in the file.
Of path, the pages of the file maintained in reminiscence aren't the identical set of pages all of the time: as clients request pages of the file that are not in reminiscence, pages which are in reminiscence are written lower back to the file on disk in the event that they were modified, or if an in-memory web page has now not been modified its buffer is conveniently used to study the brand new page.
a larger web page dimension can in the reduction of the variety of I/O operations required to method a SAS facts file. but it surely takes longer to examine a huge page than it takes to examine a small one, so until most of the observations in a large page are prone to be accessed through clients, large web page sizes can enhance the amount of time required to function I/O exercise within the server's SAS session.
There are two patterns through which information is examine from or written to SAS files:
When an utility techniques a SAS file in sequential order, no web page of the file is study into or written from the server's reminiscence greater than as soon as every time the file is examine or written. also, observations are transmitted to and from clients' periods in agencies, which conserves the messages resource.
in lots of purposes that are used with similtaneously accessed info, facts is accessed in random order, i.e., a user reads the 250th observation, then the ten,000th remark, then the fifth observation, and so forth. When a file is processed in random order, it is a whole lot extra complex to predict how again and again every web page of the file could be examine into or written from the memory of a server's SAS session. in addition, only 1 statement is transmitted on each message between server and user, which doesn't conserve the messages aid.
The "Programming strategies" part of this paper presents ideas for cutting back the I/O load of a server beneath the subject matters:
clean up your information info
opt for the appropriate subsetting approach
choose web page size accurately
Specify sequential access when an SCL program would not need random entry
a pc's working storage is used by means of a server to load courses, dangle I/O buffers, and retain control tips. When a server's working set turns into big compared to the volume of reminiscence installed on a laptop, a significant quantity of the server's working storage could be stored on disk with the aid of the working device's virtual reminiscence supervisor.
large quantities of a server's reminiscence are consumed by using:
A SAS records view that consists of an ORDER by using clause
Many indexes on facts info accessed via a server
a big variety of data open at the same time
facts info that have colossal web page sizes
considering the ORDER via clause motives the observations produced with the aid of a view to be sorted anytime the view is interpreted, it requires memory for use for a piece enviornment for the sorting step. Your software may still most effective use this clause in its views when it has a clear benefit in your clients.
When a SAS facts file is opened, all indexes on the file are opened. therefore, when a SAS records file has many indexes, a large quantity of reminiscence in the server's SAS session will also be used to shop pages of the index file and connected control suggestions. Of path, when many SAS data data which are accessed via a server each have many indexes, this impact is improved.
At SAS Institute, we have observed that most of servers' reminiscence has been consumed by I/O buffers. cautiously choosing the number of instances every file is opened by using your application and the web page dimension of each file can have considerable influence on the volume of reminiscence required by using a server.
The "Programming strategies" component of this paper presents concepts for reducing the reminiscence requirements of a server under the subject matters:
select web page measurement wisely
Index wisely
restrict the variety of data open throughout execution of an SCL program
Messages are the verbal exchange events between clients' SAS periods and a server. each time a bit of information (for example, an observation) is moved from a server to a consumer, a message is distributed from the user to the server and a reply is shipped again from the server to the consumer.
Messages and replies are transmitted with the aid of communications access methods. The can charge of a message varies vastly with access formulation. reminiscence-to-reminiscence conversation inside a single computing device, for instance by means of the pass-memory services (COMAMID=XMS) or Inter-user Communications car (COMAMID=IUCV) entry methods is very speedy, while messages that move on cables between computers, as an instance via the DECnet (COMAMID=DECNET) or TCP/IP (COMAMID=TCP) entry methods take lots longer to go back and forth between SAS classes.
SAS Institute has followed that the charge of sending records by the use of most communications access strategies is more without delay a function of the number of messages than the amount of information. In other phrases, to stream 1,000,000 characters of data between a person and a server, it takes much less time to ship the records in 100 messages than to ship the statistics in 10,000 messages.
SAS/SHARE application conserves the messages resource by using:
Transmitting records between servers and users in organizations
Evaluating where clauses in servers' sessions
interpreting SAS facts views in servers' periods
The "Programming recommendations" section of this paper offers some ideas for conserving the messages resource below the issues:
choose the acceptable subsetting method
bear in mind and handle random access
The "Tuning alternatives" part shows alternate options which you can use to control the grouping of observations on messages between servers and users:
Copyright 1999 by means of SAS Institute Inc., Cary, NC, u . s . a .. All rights reserved.
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