Tech

4月 212017
 

send an email that embeds a graphWhen using the SAS® system to email graphics output, a common request is to use SAS to send an email in which the graphics output is embedded in the body of the email. This functionality is not available until the second maintenance release for SAS® 9.4 (TS1M2). If you are using a version of SAS earlier than SAS 9.4 TS1M2, your best option is to create graphics output in a format such as RTF or PDF, and then attach the RTF or PDF file to your email.

Using the INLINED Option to Embed Graphics

If you are running SAS 9.4 TS1M2 or later, you can embed graphics output in an email. To do this, use the INLINED suboption with the ATTACH option in a SAS FILENAME statement that uses the EMAIL engine. Here is an example:

filename sendmail email to=("first.last@company.com")          from=("first.last@company.com")
    attach=("c:\temp\email.png" inlined='sgplot')
    type='text/html' subject="Emailing graphics output";

 

Then, later in your code, reference the value specified for the INLINED option in DATA step code that creates custom HTML output, as shown below:

                data _null_;  
        file sendmail;  
  put '<html>';
  put '<body>';
  put '<img src=cid:sgplot>';
  put '</body>';
  put '</html>';
run;

With this technique, although the graph is sent as an attachment, the attachment is hidden. When the email recipient opens the email, the attached graph is automatically displayed in the email (so that it looks like the graph is embedded in the body of the email).

Note: When using SAS to email graphics output, you must first set the EMAILSYS system option to SMTP and the EMAILHOST system option to the name of the SMTP email server at your site.

Embedding Multiple Graphs

You can also send multiple graphs in a single email using a SAS FILENAME statement as shown here:

            filename sendmail email to=("first.last@company.com") from=("first.last@company.com")
    attach=("c:\temp\email1.png" inlined='sgplot1'  "c:\temp\email2.png" inlined='sgplot2')
    type='text/html' subject="Emailing graphics output";

Then, create custom HTML output using DATA step code similar to the following:

     Data _null_;  
       file sendmail;  
 put '<html>';
 put '<body>';
 put '<img src=cid:sgplot1>';
 put '<img src=cid:sgplot2>';
 put '</body>';
 put '</html>';
    run;

Embedding a Graph and a PROC PRINT Table

This example shows how to embed a graph and PRINT procedure table in one email. Let us assume that you have a graph named sgplot.png stored in C:\Temp. You want to send an email using SAS that displays the SGPLOT graph in the body of the email directly before a table created with PROC PRINT. The following sample code demonstrates how to do this using a TITLE statement with PROC PRINT:

filename sendmail email  to=("first.last@company.com") from=("first.last@company.com")
     attach=("c:\temp\sgplot.png" inlined='sgplot') 
     type='text/html' subject="Email test of GRAPH output";
      ods _all_ close; 
ods html file=sendmail; 
title1 '<img src=cid:sgplot>';
proc print data=sashelp.class; 
run;
ods html close; 
ods listing; 
filename sendmail clear;

Embedding a Graph (Complete Program)

Here is a complete sample program that demonstrates embedding graphics in an email using graphics output created with the SGPLOT procedure:

%let workdir=%trim(%sysfunc(pathname(work)));
ods _ALL_ close; 
ods listing gpath="&workdir";
ods graphics / reset=index outputfmt=PNG imagename='email';  
title1 'Graph output emailed using SAS';
proc sgplot data=sashelp.cars; 
  bubble x=horsepower y=mpg_city size=cylinders;
run;
filename sendmail email to=("first.last@company.com") from=("first.last@company.com")
     attach=("&workdir./email.png" inlined='sgplot')
     type='text/html' subject="Emailing graphics output";
      data _null_;
 file sendmail;  
 put '<html>';
 put '<body>';
 put '<img src=cid:sgplot>';
 put '</body>';
 put '</html>';
run; 
      filename sendmail clear;

In conclusion, if you are running SAS 9.4 TS1M2 or later, using the INLINED option in a FILENAME statement is an excellent option when emailing graphics output.  Note that you can use this technique to email any graphics file in PNG, GIF, or JPEG format created with the SAS SG procedures, ODS Graphics, or SAS/GRAPH® procedures (such as GPLOT and GCHART).  You can also use this technique to email graphics files created with software other than SAS.

Use SAS to send an email that embeds a graph in the body of the email was published on SAS Users.

4月 182017
 

In addition to his day job as Chief Technology Officer at SAS, Oliver Schabenberger is a committed lifelong learner. During his opening remarks for the SAS Technology Connection at SAS Global Forum 2017, Schabenberger confessed to having a persistent nervous curiosity, and insisted that he’s “learning every day.” And, he encouraged attendees to do the same, officially proclaiming lifelong learning as a primary theme of the conference and announcing a social media campaign to explore the issue with attendees.

This theme of lifelong learning served a backdrop – figuratively at first, literally once the conference began! – when Schabenberger, R&D Vice President Oita Coleman and Senior R&D Project Manager Lisa Morton sat down earlier this year to determine the focus for the Catalyst Café at SAS Global Forum 2017.

A centerpiece of SAS Global Forum’s Quad area, the Catalyst Café is an interactive space for attendees to try out new SAS technology and provide SAS R&D with insight to help guide future software development. At its core, the Catalyst Café is an incubator for innovation, making it the perfect place to highlight the power of learning.

After consulting with SAS Social Media Manager Kirsten Hamstra and her team, Schabenberger, Coleman and Morton decided to explore the theme by asking three questions related to lifelong learning, one a day during each day of the conference. Attendees, and others following the conference via social media channels, would respond using the hashtag #lifelearner. Morton then visualized the responses on a 13-foot-long by 8-foot-high wall, appropriately titled the Social Listening Mural, for all to enjoy during the event.

Questions for a #lifelearner

The opening day of the conference brought this question:

Day two featured this question:

Finally, day three, and this question:

"Committed to lifelong learning"

Hamstra said the response from the SAS community was overwhelming, with hundreds of individuals contributing.

Morton working on the Social Listening Mural at the SAS Global Forum Catalyst Café

“It was so interesting to see what people shared as their first jobs,” said Morton. “One started out as a bus boy and ended up a CEO, another went from stocking shelves to analytical consulting, and a couple said they immediately started their analytical careers by becoming data analysts right out of school.”

The “what do you want to learn next?” question brought some interesting responses as well. While many respondents cited topics you’d expect from a technically-inclined crowd – things like SAS Viya, the Go Programming Language and SASPy – others said they wanted to learn Italian, how to design websites or teach kids how to play soccer.

Morton said the connections that were made during the process was fascinating and made the creation of the mural so simple and inspiring. “The project showed me how incredibly diverse our SAS users are and what a wide variety of backgrounds and interests they have.”

In the end, Morton said she learned one thing for sure about SAS users: “It’s clear our users are just as committed to lifelong learning as we are here at SAS!”

My guess is that wherever you’ll find Schabenberger at this moment – writing code in his office, behind a book at the campus library, or discussing AI with Dr. Goodnight – he’s nodding in agreement.

The final product

Nurturing the #lifelearner in all of us was published on SAS Users.

4月 172017
 

In this post, I will explain how LASR Servers (both Distributed and Non-distributed) are started from the SAS Visual Analytics Administrator application. We will also look at one particular issue and I will provide you with more details to understand the situation and two strategies to address this issue.

When you start a LASR Server from the Visual Analytics Administrator application, the system processes your request in slightly different ways depending on whether you are starting a distributed or non-distributed LASR Server.

What happens in the background for a distributed LASR Server?

1.     The administrator starts a LASR Server from the Visual Analytics Administrator application.

2.     The Visual Analytics Administrator application generates the required code and sends it to the JES to be executed on the SAS Visual Analytics Root Node.

3.     The JES invokes the SAS Object Spawner on the Visual Analytics Root Node.

4.     The SAS Object Spawner initializes a SAS Workspace Server session.

5.     A client connection is established between the JES and the SAS Workspace Server session.
The JES sends the distributed LASR Server startup code generated in step 2, and the SAS Workspace Server session executes it.

6.     As soon as the distributed LASR Server startup code is executed, a distributed LASR Server instance is created. This instance is independent from the SAS Workspace Server session.
After the distributed LASR Server startup code executes, the SAS Workspace Server session, and the client connection drop down. But the LASR Server instance is up and persistent until the administrator stops it.

What happens for a non-distributed LASR Server?

1.     The administrator starts a LASR Server from the Visual Analytics Administrator application.

2.     The Visual Analytics Administrator application generates the required code and sends it to the JES to be executed on the SAS Visual Analytics Root Node.

3.     The JES invokes the SAS Object Spawner on the Visual Analytics Root Node.

4.     The SAS Object Spawner initializes a SAS Workspace Server session.

5.     A client connection is established between the JES and the SAS Workspace Server session.
The JES sends the non-distributed LASR Server startup code generated on step 2, and the SAS Workspace Server session executes it.

6.     As soon as the non-distributed LASR Server startup code is executed, a non-distributed LASR Server instance is created. This instance is dependent on the SAS Workspace Server session.
After the distributed LASR Server startup code executes, the SAS Workspace Server session, and the client connection become persistent until the administrator stops the non-distributed LASR Server.
The SAS Workspace Server session and the client connection are required for the non-distributed LASR Server to be up and persistent.

Potential non-distributed LASR Server issue

The client connection between the JES and the SAS Workspace Server session in non-distributed deployment is crucial. This connection has to be persistent during the non-distributed LASR Server lifetime. As soon as the JES or SAS Workspace Server session goes down, the client connection is broken and the non-distributed LASR Server will go down as well. And, its data become unavailable.

If administrators manage their SAS non-distributed LASR Servers from the SAS Visual Analytics Administrator web application, this will create a dependency between the non-distributed LASR Servers and the middle tier - more specifically with the SASServer1_1 instance (the sas.wip.soapservices application). This dependency does not exist for distributed LASR Servers.

When the dependency exists, each time the middle tier or the SASServer1_1 instance is down, all non-distributed LASR Servers that were managed using the SAS Visual Analytics Administrator will go down automatically because the client connection to the non-distributed LASR Server is broken and its associated SAS Workspace Server session will go down.

This issue will also appear if the network connection between the Middle Tier and the SAS Visual Analytics Root Node is broken. This will break the client connection and terminate the SAS Workspace Server session(s) and their associated non-distributed LASR Server(s).

How can we prevent the issue?

I can think of at least two techniques you can use to prevent the dependency of your non-distributed LASR Servers upon your middle-tier:

  • Start your non-distributed LASR Servers from a SAS program.
  • Configure your LASR Server to start using the AutoLoad facility.

Start your non-distributed LASR Server from a SAS program

Here is a sample program that you might use to start a non-distributed LASR Server:

/* Start the LASR Analytic Server by defining the LASR library*/
libname LASRLIB SASIOLA 
        startserver  host="sasserver01.race.sas.com" port=10013
        signer="sasserver05.race.sas.com:7980/SASLASRAuthorization";
 
/* Keep the SAS session up until SERVERTERM received */
proc vasmp;
   serverwait  port=10013;
quit;

 

This program could be scheduled or set as a service under UNIX or Windows to be executed as soon as SAS Visual Analytics is started/restarted. Whichever strategy you use, you will want to have the code run after these services are up and available:

The SAS Metadata Server.
The Object Spawner on the SAS Visual Analytics Root Node.
The SASLASRAuthaurization service on the Middle Tier:

Start the non-distributed LASR Server Using the AutoLoad capability

AutoLoad runs as a periodic scheduled task. In the standard configuration, a new run of AutoLoad is started every 15 minutes.
AutoLoad periodically scans the contents of a designated host directory, which is referred to as the AutoLoad data directory or drop zone.
AutoLoad will automatically start the associated SAS LASR Server, if it is not yet started.

If you do not already have a LASR library configured with AutoLoad, you will need to use the SAS Deployment Manager application to configure an AutoLoad directory.

In Administration Tasks, choose Configure an AutoLoad Directory for SAS Visual Analytics. And follow the instructions.

Once you have AutoLoad setup, you must make sure certain LASR Library Extended Attributes are set correctly to ensure that the AutoLoad process will automatically start your LASR Server. You will want to set/verify the following attributes for the LASR library:

  • To enable the LASR Server AutoStart only:

  • VA.AutoLoad.AutoStart: YES to indicate that you want the associated LASR Server to be started if it is not already running.
  • VA.AutoLoad.Enabled: YES to enable the AutoLoad process for the Library.
  • To enable the LASR table(s) AutoLoad (optional):

  • VA.Default.MetadataFolder: to relocate the table(s) metadata registration against a specific metadata folder.
  • VA.Default.Location: to specify the location of the table directory at OS level.
  • VA.Default.Sync.*: to manage the table(s) from the VA.Default.Location.

On your SAS Visual Analytics machine, you have to:

  • Set the appropriate security against the [SAS-Configuration-Directory]/Levn/Applications/AutoLoad/[Your-LASR-Server-Library-LibRef] to be sure that the appropriate LASR Server administrator will be allowed to manage it.
  • Set the AutoLoad process frequency (default is 15 minutes).
    “TIME_INTERVAL_MINUTES=[Your-Value]” in the [SAS-Configuration-Directory]/Levn/Applications/AutoLoad/[Your-LASR-Server-Library-LibRef]/schedule.[sh|bat] file.
    Note: Reference the SAS Visual Analytics Administration Guide for more about  the timing of AutoLoad.
  • Schedule the AutoLoad process using the LASR Server administrator account responsible to manage this particular LASR Server by executing the [SAS-Configuration-Directory]/Levn/Applications/AutoLoad/[Your-LASR-Server-Library-LibRef]/schedule.[sh|bat] script.

Validate the AutoLoad setup by stopping the SAS LASR Server from SAS Visual Analytics Administrator application, or using SAS code. Wait for the “TIME_INTERVAL_MINUTES=[Your-Value]“, and look at the LASR Server status in SAS Visual Analytics Administrator application, and the AutoLoad logs in [SAS-Configuration-Directory]/Levn/Applications/AutoLoad/[Your-LASR-Server-Library-LibRef]/Logs (one log file each time the AutoLoad process is executed).

Whichever technique is used, the non-distributed LASR server will no longer be dependent on the middle-tier.

I hope this article has been helpful to you.

How LASR servers are started from SAS Visual Analytics Administrator was published on SAS Users.

4月 172017
 

In this post, I will explain how LASR Servers (both Distributed and Non-distributed) are started from the SAS Visual Analytics Administrator application. We will also look at one particular issue and I will provide you with more details to understand the situation and two strategies to address this issue.

When you start a LASR Server from the Visual Analytics Administrator application, the system processes your request in slightly different ways depending on whether you are starting a distributed or non-distributed LASR Server.

What happens in the background for a distributed LASR Server?

1.     The administrator starts a LASR Server from the Visual Analytics Administrator application.

2.     The Visual Analytics Administrator application generates the required code and sends it to the JES to be executed on the SAS Visual Analytics Root Node.

3.     The JES invokes the SAS Object Spawner on the Visual Analytics Root Node.

4.     The SAS Object Spawner initializes a SAS Workspace Server session.

5.     A client connection is established between the JES and the SAS Workspace Server session.
The JES sends the distributed LASR Server startup code generated in step 2, and the SAS Workspace Server session executes it.

6.     As soon as the distributed LASR Server startup code is executed, a distributed LASR Server instance is created. This instance is independent from the SAS Workspace Server session.
After the distributed LASR Server startup code executes, the SAS Workspace Server session, and the client connection drop down. But the LASR Server instance is up and persistent until the administrator stops it.

What happens for a non-distributed LASR Server?

1.     The administrator starts a LASR Server from the Visual Analytics Administrator application.

2.     The Visual Analytics Administrator application generates the required code and sends it to the JES to be executed on the SAS Visual Analytics Root Node.

3.     The JES invokes the SAS Object Spawner on the Visual Analytics Root Node.

4.     The SAS Object Spawner initializes a SAS Workspace Server session.

5.     A client connection is established between the JES and the SAS Workspace Server session.
The JES sends the non-distributed LASR Server startup code generated on step 2, and the SAS Workspace Server session executes it.

6.     As soon as the non-distributed LASR Server startup code is executed, a non-distributed LASR Server instance is created. This instance is dependent on the SAS Workspace Server session.
After the distributed LASR Server startup code executes, the SAS Workspace Server session, and the client connection become persistent until the administrator stops the non-distributed LASR Server.
The SAS Workspace Server session and the client connection are required for the non-distributed LASR Server to be up and persistent.

Potential non-distributed LASR Server issue

The client connection between the JES and the SAS Workspace Server session in non-distributed deployment is crucial. This connection has to be persistent during the non-distributed LASR Server lifetime. As soon as the JES or SAS Workspace Server session goes down, the client connection is broken and the non-distributed LASR Server will go down as well. And, its data become unavailable.

If administrators manage their SAS non-distributed LASR Servers from the SAS Visual Analytics Administrator web application, this will create a dependency between the non-distributed LASR Servers and the middle tier - more specifically with the SASServer1_1 instance (the sas.wip.soapservices application). This dependency does not exist for distributed LASR Servers.

When the dependency exists, each time the middle tier or the SASServer1_1 instance is down, all non-distributed LASR Servers that were managed using the SAS Visual Analytics Administrator will go down automatically because the client connection to the non-distributed LASR Server is broken and its associated SAS Workspace Server session will go down.

This issue will also appear if the network connection between the Middle Tier and the SAS Visual Analytics Root Node is broken. This will break the client connection and terminate the SAS Workspace Server session(s) and their associated non-distributed LASR Server(s).

How can we prevent the issue?

I can think of at least two techniques you can use to prevent the dependency of your non-distributed LASR Servers upon your middle-tier:

  • Start your non-distributed LASR Servers from a SAS program.
  • Configure your LASR Server to start using the AutoLoad facility.

Start your non-distributed LASR Server from a SAS program

Here is a sample program that you might use to start a non-distributed LASR Server:

/* Start the LASR Analytic Server by defining the LASR library*/
libname LASRLIB SASIOLA 
        startserver  host="sasserver01.race.sas.com" port=10013
        signer="sasserver05.race.sas.com:7980/SASLASRAuthorization";
 
/* Keep the SAS session up until SERVERTERM received */
proc vasmp;
   serverwait  port=10013;
quit;

 

This program could be scheduled or set as a service under UNIX or Windows to be executed as soon as SAS Visual Analytics is started/restarted. Whichever strategy you use, you will want to have the code run after these services are up and available:

The SAS Metadata Server.
The Object Spawner on the SAS Visual Analytics Root Node.
The SASLASRAuthaurization service on the Middle Tier:

Start the non-distributed LASR Server Using the AutoLoad capability

AutoLoad runs as a periodic scheduled task. In the standard configuration, a new run of AutoLoad is started every 15 minutes.
AutoLoad periodically scans the contents of a designated host directory, which is referred to as the AutoLoad data directory or drop zone.
AutoLoad will automatically start the associated SAS LASR Server, if it is not yet started.

If you do not already have a LASR library configured with AutoLoad, you will need to use the SAS Deployment Manager application to configure an AutoLoad directory.

In Administration Tasks, choose Configure an AutoLoad Directory for SAS Visual Analytics. And follow the instructions.

Once you have AutoLoad setup, you must make sure certain LASR Library Extended Attributes are set correctly to ensure that the AutoLoad process will automatically start your LASR Server. You will want to set/verify the following attributes for the LASR library:

  • To enable the LASR Server AutoStart only:

  • VA.AutoLoad.AutoStart: YES to indicate that you want the associated LASR Server to be started if it is not already running.
  • VA.AutoLoad.Enabled: YES to enable the AutoLoad process for the Library.
  • To enable the LASR table(s) AutoLoad (optional):

  • VA.Default.MetadataFolder: to relocate the table(s) metadata registration against a specific metadata folder.
  • VA.Default.Location: to specify the location of the table directory at OS level.
  • VA.Default.Sync.*: to manage the table(s) from the VA.Default.Location.

On your SAS Visual Analytics machine, you have to:

  • Set the appropriate security against the [SAS-Configuration-Directory]/Levn/Applications/AutoLoad/[Your-LASR-Server-Library-LibRef] to be sure that the appropriate LASR Server administrator will be allowed to manage it.
  • Set the AutoLoad process frequency (default is 15 minutes).
    “TIME_INTERVAL_MINUTES=[Your-Value]” in the [SAS-Configuration-Directory]/Levn/Applications/AutoLoad/[Your-LASR-Server-Library-LibRef]/schedule.[sh|bat] file.
    Note: Reference the SAS Visual Analytics Administration Guide for more about  the timing of AutoLoad.
  • Schedule the AutoLoad process using the LASR Server administrator account responsible to manage this particular LASR Server by executing the [SAS-Configuration-Directory]/Levn/Applications/AutoLoad/[Your-LASR-Server-Library-LibRef]/schedule.[sh|bat] script.

Validate the AutoLoad setup by stopping the SAS LASR Server from SAS Visual Analytics Administrator application, or using SAS code. Wait for the “TIME_INTERVAL_MINUTES=[Your-Value]“, and look at the LASR Server status in SAS Visual Analytics Administrator application, and the AutoLoad logs in [SAS-Configuration-Directory]/Levn/Applications/AutoLoad/[Your-LASR-Server-Library-LibRef]/Logs (one log file each time the AutoLoad process is executed).

Whichever technique is used, the non-distributed LASR server will no longer be dependent on the middle-tier.

I hope this article has been helpful to you.

How LASR servers are started from SAS Visual Analytics Administrator was published on SAS Users.

4月 132017
 
The Penitent Magdalene

Titian (Tiziano Vecellio) (Italian, about 1487 - 1576) The Penitent Magdalene, 1555 - 1565, Oil on canvas 108.3 × 94.3 cm (42 5/8 × 37 1/8 in.) The J. Paul Getty Museum, Los Angeles; Digital image courtesy of the Getty's Open Content Program.

Even if you are a traditional SAS programmer and have nothing to do with cybersecurity, you still probably have to deal with this issue in your day-to-day work.

The world has changed, and what you do as a SAS programmer is not just between you and your computer anymore. However, I have found that many of us are still careless, negligent or reckless enough to be dangerous.

Would you scotch-tape your house key to the front door next to the lock and go on vacation? Does anybody do that? Still, some of us have no problem explicitly embedding passwords in our code.

That single deadly sin, the thing that SAS programmers (or any programmers) must not do under any circumstances, is placing unmasked passwords into their code. I must confess, I too have sinned, but I have seen the light and hope you will too.

Password usage examples

Even if SAS syntax calls for a password, never type it or paste it into your SAS programs. Ever.

If you connect to a database using a SAS/ACCESS LIBNAME statement, your libname statement might look like:

libname mydblib oracle path=airdb_remote schema=hrdept
	user=myusr1 password=mypwd1;

If you specify the LIBNAME statement options for the metadata engine to connect to the metadata server, it may look like:

libname myeng meta library=mylib
	repname=temp metaserver='a123.us.company.com' port=8561 
 		user=idxyz pw=abcdefg;

If you use LIBNAME statement options for the metadata engine to connect to a database, it may look like:

libname oralib meta library=oralib dbuser=orauser dbpassword=orapw;

In all of the above examples, some password is “required” to be embedded in the SAS code. But it does not mean you should put it there “as is,” unmasked. SAS program code is usually saved as a text file, which is stored on your laptop or somewhere on a server. Anyone who can get access to such a file would immediately get access to those passwords, which are key to accessing databases that might contain sensitive information. It is your obligation and duty to protect this sensitive data.

Hiding passwords in a macro variable or a macro?

I’ve seen some shrewd SAS programmers who do not openly put passwords in their SAS code. Instead of placing the passwords directly where the SAS syntax calls for, they assign them to a macro variable in AUTOEXEC.SAS, an external SAS macro file, a compiled macro or some other SAS program file included in their code, and then use a macro reference, e.g.

/* in autoexec.sas or external macro */
%let opw = mypwd1;
 
/* or */
 
%macro opw;
	mypwd1
%mend opw;
/* in SAS program */
libname mydblib oracle user=myusr1 password=&opw
        path=airdb_remote schema=hrdept;
 
/* or */
 
libname mydblib oracle user=myusr1 password=%opw
        path=airdb_remote schema=hrdept;

Clever! But it’s no more secure than leaving your house key under the door mat. In fact it is much less secure. One who wants to look up your password does not even need to look under the door mat, oh, I mean look at your program file where the password is assigned to a macro variable or a macro. For a macro variable, a simple %put &opw; statement will print the password’s actual value in the SAS log. In case of a macro, one can use %put %opw; with the same result.

In other words, hiding the passwords do not actually protect them.

What to do

What should you do instead of openly placing or concealing those required passwords into your SAS code? The answer is short: encrypt passwords.

SAS software provides a powerful procedure for encrypting passwords that renders them practically unusable outside of the SAS system.

This is PROC PWENCODE, and it is very easy to use. In its simplest form, in order to encrypt (encode) your password abc123 you would need to submit just the following two lines of code:

proc pwencode in="abc123";
run;

The encrypted password is printed in the SAS log:

1 proc pwencode in=XXXXXXXX;
2 run;

{SAS002}3CD4EA1E5C9B75D91A73A37F

Now, you can use this password {SAS002}3CD4EA1E5C9B75D91A73A37F in your SAS programs. The SAS System will seamlessly take care of decrypting the password during compilation.

The above code examples can be re-written as follows:

libname mydblib oracle path=airdb_remote schema=hrdept
	user=myusr1 password="{SAS002}9746E819255A1D2F154A26B7";
 
libname myeng meta library=mylib
	repname=temp metaserver='a123.us.company.com' port=8561 
 		user=idxyz pw="{SAS002}9FFC53315A1596D92F13B4CA";
 
libname oralib meta library=oralib dbuser=orauser
dbpassword="{SAS002}9FFC53315A1596D92F13B4CA";

Encryption methods

The {SAS002} prefix indicates encoding method. This SAS-proprietary encryption method which uses 32-bit key encryption is the default, so you don’t have to specify it in the PROC PWENCODE.

There are other, stronger encryption methods supported in SAS/SECURE:

{SAS003} – uses a 256-bit key plus 16-bit salt to encode passwords,

{SAS004} – uses a 256-bit key plus 64-bit salt to encode passwords.

If you want to encode your password with one of these stronger encryption methods you must specify it in PROC PWENCODE:

proc pwencode in="abc123" method=SAS003;
run;

SAS Log: {SAS003}50374C8380F6CDB3C91281FF2EF57DED10E6

proc pwencode in="abc123" method=SAS004;
run;

SAS Log: {SAS004}1630D14353923B5940F3B0C91F83430E27DA19164FC003A1

Beyond encryption

There are other methods of obscuring passwords to protect access to sensitive information that are available in the SAS Business Intelligence Platform. These are the AUTHDOMAIN= SAS/ACCESS option supported in LIBNAME statements, as well as PROC SQL CONNECT statements, SAS Token Authentication, and Integrated Windows Authentication. For more details, see Five strategies to eliminate passwords from your SAS programs.

Conclusion

Never place unencrypted password into your SAS program. Encrypt it!

Place this sticker in front of you until you memorize it by heart.

PROC PWENCODE sticker

 

One deadly sin SAS programmers should stop committing was published on SAS Users.

4月 112017
 

You may be wondering if you need something special to gain access to the Schedule Chart object. Don’t worry, you don’t, you just need to unhide this visualization if it isn’t already. You can do this from the Objects’ drop down menu. There are several other objects available to you if you’d like to show those as well. Simply check the ones you want to include in the list and then click ok.

The VA 7.3 Schedule Chart is similar to the traditional Gantt chart in that it serves to illustrate the start and finish duration of a category data item. You must provide a category data item and two date or datetime data items representing the start and end dates. You can also add a group by category, lattice by columns and/or rows.   Here is a simple example that visualizes my local school district’s 2016-2017 Traditional School Calendar.

Schedule charts can be used to visualize a variety of data such as:

  • Calendar Events
  • Project Tracking
  • Campaign/Promotional Runs
  • Floor Service Coverage

Essentially, any category which can be associated with a start and end date can use this visualization.

Here are some examples of using the Schedule Chart to look at project tracking data. Our team uses a similar visualization; however, I have modified real names and gave it a Star Wars theme for a bit of fun.

Example 1

In this example, the Project name is assigned as the main category. Here are a few takeaways:

  • The schedule chart gives a great bird’s eye view of a lot of data. This particular data has over 350 projects spanning a team of 19 individual members.
  • The schedule chart automatically includes the least and greatest date value. You can override the X Axis in the Properties tab by assigning a fixed minimum and maximum.

In this next screenshot, I have selected the manager Obi-Wan Kenobi to filter the Schedule Chart. Therefore, by adding section filters to this report, you can see how spotting coverage of Projects and Project Types are easy. And, with some Mock Combat planned later in the year, the Jedis might want to up their training.

Example 2

This example uses the same Schedule Chart role assignments as before, but different section prompt filters. Here, this report shows how an individual team member can use the Schedule Chart to visualize several things:

  • A list of his/her assigned projects.
  • The planned duration of each project.
  • How the projects are spread throughout the year.

If you chose to look at a particular Project Type, then this visualization would help list the Project names and how they span across the year.

Example 3

The next example moves away from the traditional use of putting the Project as the main category data item and instead places the Team Lead on the Y Axis. This now allows us to see how busy each Team member is and with which Project Type. By the way, did you notice the neat way the Team names are sorted? I used a custom sort!

Here are just a few more things you can do to enhance this visualization: you can adjust the transparency so you can see overlapping projects and you can easily add reference lines to the X Axis. In this example, I’ve added the reference lines for Q1 through Q4. I’ve also selected a manager from the report section filters and added an additional data item for the Label.

Example 4

In this example, I wanted to demonstrate the use of the Lattice rows and I also applied a Display Rule for the Project Type. This is a good way if you want to view overlapping information and the transparency property isn’t distinct enough.

 

Schedule Chart Limitations

If you want a bar representation on the Schedule Chart to appear then the data must have a start and end date for every row of data. If either is missing, then the category name will appear on the Y Axis but no bar will be displayed on the visualization.   Also, you cannot create an interaction from or to the Schedule Chart object. That means you cannot create a filter or brush with another object in the report area. The Schedule Chart will be filtered by either report or section prompts.   I hope you can include the Schedule Chart into your reports, it is one of my favorite visuals.

SAS Visual Analytics Designer 7.3 Schedule Chart was published on SAS Users.

4月 102017
 

You can expand on the functionality of SAS Visual Data Builder in SAS Visual Analytics by editing the query code, adding code for pre- and post-processing, or even writing your own query.   You can process single tables or join multiple tables, writing the output to a LASR  library, a SAS library, or a DBMS library.  But you can also easily schedule your queries, right from the Visual Data Builder interface.

Here’s how.

When a query is open in the workspace of Visual Data Builder, you can schedule the query from the application by clicking the Schedule (clock) icon.

The scheduling server used is determined by the SAS Visual Data Builder Scheduling preferences setting, shown below.

By default, the Visual Analytics deployment includes the Operating System Services scheduling server, so it appears automatically as the default.

The Server Manager plug-in to SAS Management Console identifies the scheduling servers that are included in your deployment. You can specify a different scheduling server, such as Platform Suite for SAS server, if your deployment includes it.

Note:  The Distributed In-process scheduling server is not supported.

Any scheduling preferences that you change are used the next time you create and schedule a query. If you need to change the settings for a query that is already scheduled, you can use SAS Management Console Schedule Manager to redeploy the deployed job for the query.

When you schedule a query, the SAS statements are saved in a file in the default deployment directory path: SAS-config-dir/Lev1/SASApp/SASEnvironment/SASCode/Jobs.

In the examples in this blog, the SAS-config-dir is /opt/sasinside/vaconfig.
The metadata name of the directory is Batch Jobs.
The default SAS Application Server name associated with the directory is SASApp.

If you are working in a VA environment where multiple application servers are defined, you should be aware of the following SAS Notes at the links below, relating to the application’s choice of application servers for scheduling.

SAS Note 58186SAS® Visual Data Builder might use the wrong application server for scheduling
SAS Note 52977SAS® Visual Data Builder requires the default SAS® Application Server and the default scheduling servers to be located on the same physical machine

To schedule a query, open the query and select the Schedule (clock) icon. (The clock is grayed out if you have not saved the query.)

You can schedule the query to run immediately (Run now) or at a specified time event.  To define a time event, select the Select one or more triggers for this query button and click New Time Event.  Grouping events are not supported for the default server, but may be supported for other scheduling servers, such as Platform Suite.

You can schedule for One time only, or More than once, running Hourly, Daily, Weekly, Monthly, or Yearly.  The appearance of the interface and scheduling parameters change with your specification.

In this example, a One time only event is specified.

 

The time event specification gets recorded in the Trigger list on the Schedule page, and is selected in the Used column.

After you click OK in the Schedule window, you will get the confirmation below.

After the time event has passed, you can verify that the table has been loaded on the LASR Tables tab of the Visual Analytics Administrator.

When you schedule, the Visual Data Builder:

  • creates a job that executes the query.
  • creates a deployed job from the job.
  • places the job into a new deployed flow.
  • schedules the flow on a scheduling server.

The files are named according to vdb_query_id_timestamp.
In this example the files are named vdb_CustomerInfoData_1490112883364_timestamp.
When the query executes at the scheduled time, the SAS code that is written to the /opt/sasinside/vaconfig/Lev1/SASApp/SASEnvironment/SASCode/Jobs directory.  The query is run with the user ID that scheduled it.

If you right-click on Server Manager in SAS Management Console and view Deployment Directories, you will see that this is the Deployment directory (Batch Jobs) for SASApp.

In the /opt/sasinside/vaconfig/Lev1/SASApp/BatchServer/Logs directory, you can view the SAS Log.

The scheduling server script and log are in /opt/sasinside/vaconfig/Lev1/SchedulingServer/Ahmed/vdb_CustomerInfoData_14900112883364

Observe that the script was written to this location at the time the job was scheduled, rather than at execution time.

If you edit a data query that is already scheduled, you must click the schedule icon again so that the SAS statements for the data query are regenerated and saved.

If you edit the query again and specify additional time events, each event appears in the trigger list, and you can check which time event is to be used for scheduling.

If scheduling a query according to time events, you should also be aware of this Usage note:

Usage Note 55880: Scheduled SAS® Visual Data Builder queries are executed based on the time zone of the scheduling server 

And to add to the fun, also keep in mind that if your deployment includes SAS Data Integration Studio, you can also export a query as a Job and then perform the deployment steps using DI Studio.

Just right-click on the query in the SAS folder panel in Visual Data Builder and Select Export as a Job!

Easy Scheduling in Visual Data Builder - SAS Visual Analytics 7.3 was published on SAS Users.

4月 052017
 

Emma Warrillow, President of Data Insight Group, Inc., believes analysts add business value when they ask questions of the business, the data and the approach. “Don’t be an order taker,” she said.

Emma Warrillow at SAS Global Forum.

Warrillow held to her promise that attendees wouldn’t see a stitch of SAS programming code in her session Monday, April 3, at SAS Global Forum.

Not that she doesn’t believe programming skills and SAS Certifications aren’t important. She does.

Why you need communication skills

But Warrillow believes that as technology takes on more of the heavy lifting from the analysis side, communication skills, interpretation skills and storytelling skills are quickly becoming the data analyst’s magic wand.

Warrillow likened it to the centuries-old question: If a tree falls in a forest, and no one is around to hear it, did it make a sound? “If you have a great analysis, but no one gets it or takes action, was it really a great analysis?” she asked.


If you have a great analysis, but no one gets it or takes action, was it really a great analysis?
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To create real business value and be the unicorn – that rare breed of marketing technologist who understands both marketing and marketing technology – analysts have to understand the business and its goals and operations.

She offered several actionable tips to help make the transition, including:

1. Never just send the spreadsheet.

Or the PowerPoint or the email. “The recipient might ignore it, get frustrated or, worse yet, misinterpret it,” she said. “Instead, communicate what you’ve seen in the analysis.”

2. Be a POET.

Warrillow is a huge fan of the work of Laura Warren of Storylytics.ca. who recommends an acronym approach to data-based storytelling and making sure every presentation offers:

  • Purpose: The purpose of this chart is to …
  • Observation: To illustrate that …
  • Explanation: What this means to us is …
  • Take-away or Transition: As a next step, we recommend …

3. Brand your work.

“Many of us suffer from a lack of profile in our organizations,” she said. “Take a lesson from public relations and brand yourselves. Just make sure you’re a brand people can trust. Have checks and balances in place to make sure your data is accurate.”

4. Don’t be an order taker.

Be consultative and remember that you are the expert when it comes to knowing how to structure the campaign modeling. It can be tough in some organizations, Warrillow admitted, but asking some questions and offering suggestions can be a great way to begin.

5. Tell the truth.

“Storytelling can be associated with big, tall tales,” she said. “You have to have stories that are compelling but also have truth and resonance.” One of her best resources is The Four Truths of the Storyteller” by Peter Gruber, which first appeared in Harvard Business Review December 2007.

6. Go higher.

Knowledge and comprehension are important, “but we need to start moving further up the chain,” Warrillow said. She used Bloom’s Taxonomy to describe the importance of making data move at the speed of business – getting people to take action by moving into application, analysis, synthesis and evaluation phases.

7. Prepare for the future.

“Don’t become the person who says, ‘I’m this kind of analyst,’” she said. “We need to explore new environments, prepare ourselves with great skills. In the short term, we’re going to need more programming skills. Over time, however, we’re going to need interpretation, communication and storytelling skills.” She encouraged attendees to answer the SAS Global Forum challenge of becoming a #LifeLearner.

For more from Warrillow, read the post, Making data personal: big data made small.

7 tips for becoming a data science unicorn was published on SAS Users.

4月 032017
 

At Opening Session, SAS CEO Jim Goodnight and Alexa have a chat using the Amazon Echo and SAS Visual Analytics.

Unable to attend SAS Global Forum 2017 happening now in Orlando? We’ve got you covered! You can view live stream video from the conference, and check back here for important news from the conference, starting with the highlights from last night’s Opening Session.

While the location and record attendance made for a full house this year, CEO Jim Goodnight explained that there couldn’t be a more perfect setting to celebrate innovation than the world of Walt Disney. “Walt was a master innovator, combining art and science to create an entirely new way to make intelligent connections,” said Goodnight. “SAS is busy making another kind of intelligent connection – the kind made possible by data and analytics.”

It’s SAS’ mission to bring analytics everywhere and to make it ambient. That was exactly the motivation that drove SAS nearly four years ago when embarking on a massive undertaking known as SAS® Viya™. But SAS Viya – announced last year in Las Vegas – is more than just a fast, powerful, modernized analytics platform. Goodnight said it’s really the perfect marriage of science and art.

“Consider what would be possible if analytics could be brought into every moment and every place that data exists,” said Goodnight. “The opportunities are enormous, and like Walt Disney, it’s kind of fun to do the impossible.”

Driving an analytics economy

Executive Vice President and Chief Marketing Officer Randy Guard took the stage to update attendees on new releases available on SAS Viya and why SAS is so excited about it. And he explained the reason for SAS Viya comes from the changes being driven in the analytics marketplace. It’s what Guard referred to as an analytics economy – where the maturity of algorithms and techniques progress rapidly. “This is a place where disruption is normal, a place where you want to be the disruptor; you want to be the innovator,” said Guard. That’s exactly what you can achieve with SAS Viya.

As if SAS Viya didn’t leave enough of an impression, Guard took it one step further by inviting Goodnight back on stage to give users a preview into the newest innovation SAS has been cooking up. Using the Amazon Echo Dot – better known as Alexa – Goodnight put cognitive computing into action as he called up annual sales, forecasts and customer satisfaction reports in SAS® Visual Analytics.

Though still in its infant stages of development, the demo was just another reminder that when it comes to analytics, SAS never stops thinking of the next great thing.

AI: The illusion of intelligence

On his Segway, Executive Vice President and Chief Technology Officer Oliver Schabenberger talks AI at the SAS Global Forum Opening Session.

With his Segway Mini, Executive Vice President and Chief Technology Officer Oliver Schabenberger rolled on stage, fully trusting that his “smart legs” wouldn’t drive him off and into the audience. “I’ve accepted that algorithms and software have intelligence; I’ve accepted that they make decisions for us, but we still have choices,” said Schabenberger.

Diving into artificial intelligence, he explained that today’s algorithms operate with super-human abilities – they are reliable, repeatable and work around the clock without fatigue – yet they don’t behave like humans. And while the “AI” label is becoming trendy, true systems deserving of the AI title have two distinct things in common: they belong to the class of weak AI systems and they tend to be based on deep learning.

So, why are those distinctions important? Schabenberger explained that a weak AI system is trained to do one task only – the system driving an autonomous vehicle cannot operate the lighting in your home.

“SAS is very much engaged in weak AI, building cognitive systems into our software,” he said. “We are embedding learning and gamification into solutions and you can apply deep learning to text, images and time series.” Those cognitive systems are built into SAS Viya. And while they are powerful and great when they work, Schabenberger begged the question of whether or not they are truly intelligent.

Think about it. True intelligence requires some form of creativity, innovation and independent problem solving. The reality is, that today’s algorithms and software, no matter how smart, are being used as decision support systems to augment our own capabilities and make us better.

But it’s uncomfortable to think about fully trusting technology to make decisions on our behalf. “We make decisions based on reason, we use gut feeling and make split-second judgment calls based on incomplete information,” said Schabenberger. “How well do we expect machines to perform [in our place]when we let them loose and how quickly do we expect them to learn on the job?”

It’s those kinds of questions that prove that all we can handle today is the illusion of intelligence. “We want to get tricked by the machine in a clever way,” said Schabenberger. “The rest is just hype.”

Creating tomorrow‘s analytics leaders

With a room full of analytics leaders, Vice President of Sales Emily Baranello asked attendees to consider where the future leaders of analytics will come from. If you ask SAS, talent will be pulled from universities globally that have partnered with SAS to create 200 types of programs that teach today’s students how to work in SAS software. The commitment level to train up future leaders is evident and can be seen in SAS certifications, joint certificate programs and SAS’ track toward nearly 1 million downloads of SAS® Analytics U.

“SAS talent is continuing to building in the marketplace,” said Baranello. “Our goal is to bring analytics everywhere and we will continue to partner with universities to ready those students to be your successful employees.”

Using data for good

More than just analytics and technology, SAS’ brand is a representation of people who make the world a better place. Knowing that, SAS announced the development of GatherIQ – a customized crowdsourcing app that will begin with two International Organization for Migration (IMO) projects. One project will specifically focus on global migration, using data to keep migrants safe as they search for a better life. With GatherIQ, changing the world might be as easy as opening an app.

There's much more to come, so stay tuned to SAS blogs this week for the latest updates from SAS Global Forum!

SAS Viya, AI star at SAS Global Forum Opening Session was published on SAS Users.

4月 012017
 

Solar farm on SAS campus The full text of Fermat's statement, written in Latin, reads "Cubum autem in duos cubos, aut quadrato-quadratum in duos quadrato-quadratos, et generaliter nullam in infinitum ultra quadratum potestatem in duos eiusdem nominis fas est dividere cuius rei demonstrationem mirabilem sane detexi. Hanc marginis exiguitas non caperet."

The English translation is: "It is impossible for a cube to be the sum of two cubes, a fourth power to be the sum of two fourth powers, or in general for any number that is a power greater than the second to be the sum of two like powers. I have discovered a truly marvelous demonstration of this proposition that this margin is too narrow to contain."

Here at SAS, we don’t take challenges lightly. After a short but intensive brainstorming, we came up with a creative and powerful SAS code that effectively proves this long-standing theorem. And it is so simple and short that not only can it be written on the margins of this blog, it can be tweeted!

Drum roll, please!

Here is the SAS code:

data _null_; 
	do n=3 by 1; 
		do a=1 by 1; 
			do b=1 by 1; 
				do c=1 by 1; 
					e = a**n + b**n = c**n;
					if e then stop; 
				end;
			end; 
		end;
	end;
run;

Or written compactly, without unnecessary spaces:

data _null_;do n=3 by 1;do a=1 by 1;do b=1 by 1;do c=1 by 1;e=a**n+b**n=c**n;if e then stop;end;end;end;end;run;

which is exactly 112 character long – well below the Twitter 140-character threshold.

Don’t be fooled by the utter simplicity and seeming unfeasibility of this code.  For the naysayers, let me clarify that we run this code in a distributed multithreaded environment where each do-loop runs as a separate thread.

We also use some creative coding techniques:

1.     Do-loop with just two options, count= and by=, but without the to= option (e.g. do c=1 by 1;). It is a valid syntax in SAS and serves the purpose of creating infinite loops when they are necessary (like in this case). You can easily test it by running the following SAS code snippet:

data _null_;
	start = datetime();
	do i=1 by 1;
		if intck('sec',start,datetime()) ge 20 then leave;
	end;
run;

The if-statement here is added solely for the purpose of specifying a wait time (e.g. 20) sufficient for persuading you in the loop’s infiniteness. Skeptics may increase this number to their comfort level or even remove (or comment out) the if-statement and enjoy the unconstrained eternity.

2.     Expression with two “=” signs in it (e.g. e = a**n + b**n = c**n;) Again, this is a perfectly valid expression in SAS and serves the purpose of assigning a variable the value of 0 or 1 resulting from a logical comparison operation. This expression can be rewritten as

e = a**n + b**n eq c**n;

or even more explicitly as

e = (a**n + b**n eq c**n);

As long as the code runs, the theorem is considered proven. If it stops, then the theorem is false.

You can try running this code on your hardware, at your own risk, of course.

We have a dedicated 128-processor UNIX server powered by an on-campus solar farm that has been autonomously running the above code for 40 years now, and there was not a single instance when it stopped running. Except pausing for the scheduled maintenance and equipment replacements.

During the course of this historic experience, we have accumulated an unprecedented amount of big data (all in-memory), converted it into event stream processing, and become a leader in data mining and business analytics.

This leads us to the following scientific conclusion: whether you are a pure mathematician or an empiricist, you can rest assured that Fermat's Last Theorem has been proven with a probability asymptotic to 1 beyond a reasonable doubt.

Have a happy 91-st day of the year 2017!

 

SAS code to prove Fermat's Last Theorem was published on SAS Users.