About RonAgresta

RonAgresta · ‎04-14-2016

Hi, Have you looked in the documentation for additional setup details? There is a "Java Plugin Node - FAQ" topic as well as a "Java Plugin Node," a "Running a Java Program in a Data Job," and "Set Up for the Java Plugin Node" topics with lots of information about setting classpath information. Ron

RonAgresta · ‎04-12-2016

It may seem counterintuitive but there are two different data access methods going on here. When you use Data Connections, you are using a Data Management Studio managed data source and by doing so this data will show up in many places like when you build a data job or perform data profiling. In a process job, when you use the SAS code node, you are actually communicating with a SAS workspace server. It won't have knowledge of the connection to SAS you established in Data Management Studio. If you want to access the same SAS table from the SAS code node, it would have to be available to your workspace server through normal means you would use to set up a connection to a data library in SAS. But you don't need to use the SAS code node to work with the data in Data Management Studio. Once you connect to it, you can use any number of the other data quality and data integration nodes to transform the data. Ron Ron

RonAgresta · ‎04-12-2016

Hi, As you have probably already figured out, work tables are used for temporary storage of data so that it can be accessed in other parts of your data job or process job. It can't be used as input for a SQL statement - at least not directly. It would be possible to read values out of a work table and store the values in macro variables that could be used as parameters to an SQL statement in other steps in your job. If your goal is to read data into your job from a csv file to then subset it in some way, you could read it in directly, skip the work table step, and use the expression node to select/filter the rows that you are interested in. Ron

RonAgresta · ‎04-08-2016

Hi, You do have options to read SAS datasets from within DataFlux Data Management Studio. You can set up a data connection to the SAS data or you can use a process job to execute SAS code. There is no way to have Data Management Studio interact directly with your EG project. Ron

RonAgresta · ‎04-02-2016

Hi Helle, If you can use the ID to identify the rows/values you want to compare, you can: Sort by the ID Use the expression node to group by that ID Start with the first description value you encounter for that group Then compare that value to subsequent description values in the group using the edit distance function Use the pushrow function to create a new row to flag that group for review. Set the option to flag the row as "pushed" Reset the initial value in between groups to start the comparison anew for each group If you then use a branch node with some filter nodes on each branch, you can capture the IDs for groups with some issues to review (filter to only keep pushed rows), and join back to the other side of the branch to limit the results to just groups with differences. If the ID can't be used to create groups, use a match code on the description value and then use a cluster node to group possible similar records, sorting after the cluster operation. Then follow the steps above but use the cluster ID instead of the ID value for groups. Ron

RonAgresta · ‎03-18-2016

Hi, Two things come to mind: Double-check to make sure the DataFlux process has permission to access the location set for temporary file I/O operations. You may also need to clean up this location. Processes that terminate unexepectedly may leave temporary files hanging around. We sometimes see errors of this kind if your system is running out of memory. Have you tried running the process on a small subset of input records? It it succeeds it may point to a memory limitation. The Join node has specifc settings for memory usage that can be adjusted (through the advanced properties screen of the node). From the documentation: Any temporary files that are generated by the job, such a sort files, are saved to the location that is specified in the BASE/TEMP option in a DataFlux configuration file, if this option has been set. If the BASE/TEMP option has not been set, temporary files will be written to the temporary file location that is specified for the operating system. To see if the BASE/TEMP option has been set, select Tools > Data Management Studio Options > Job > Advanced. Ron

RonAgresta · ‎03-14-2016

Hi, It appears you are building a data job in Data Management Studio. If you haven't already done so, try going to the "Data" riser on the left in Data Management Studio, right-click on your "PSELIV01_USER" data connection, clear and then save your user credentials. Ron

RonAgresta · ‎02-26-2016

Another SAS technology that gets data into Hadoop is SAS Data Loader for Hadoop. It doesn't just load data into Hadoop but can join, match, merge, and cleanse data there too. It's just one more option in SAS' wide array of technologies and solutions that lets you take advantage of investments made in your Hadoop infrastructure. Ron

RonAgresta · ‎02-25-2016

Hi, If the output tokens from the parse definition you have chosen to use don't meet your needs, you can use the Customize component of Data Management Studio to adjust them. You can choose to add or delete tokens but doing so may require adjustments in the pattern logic mappings to the output tokens. Take a look at the documentation for Data Management Studio and search for "Managing and Customizing QKBs." Ron

RonAgresta · ‎01-29-2016

Hi Nash, I'm not sure you'll find the information you are looking for here on the Data Management forum. Have you tried the Administration forum? If you haven't taken a look at installation informtion on the SAS support site, it may also be of some use. You can find some training on the support site as well. If you're really stuck, don't hesitate to open a support track for assistance. Ron

RonAgresta · ‎01-20-2016

SAS released new versions of core software in our Data Management portfolio recently. SAS Event Stream Processing, SAS Federation Server, and SAS Data Management have added new features or enhancements. Listed below are just a few of these improvements. SAS Federation Server 4.2 includes the following key updates: Integration with SAS Metadata Server Data masking enhancements Support for SAS DS2 Data quality transformations within FedSQL and DS2 code Apache Hive access SAS Data Management offerings (with SAS Data Management Studio 2.7 and SAS Data Management Server 2.7) include the following changes: A REST-based web service API for SAS Data Management Server FIPS security compliance settings for SAS Data Management Server SAS Event Stream Processing 3.2 additions include the following: YARN integration Dynamic ESP model changes New connectors/adaptors for Oracle logs, Greenplum logs, and Apache Camel Learning models for K-means and clustering Additional information on new features can be found in product documentation located here: SAS Data Management Offerings SAS Federation Server 4.2 SAS Event Stream Processing 3.2 There are tons of new features across SAS' Data Management suite of products. Dive in, try them out, and let us know what you think. Ron

RonAgresta · ‎01-19-2016

Hi, From within an expression node, you can't hide columns coming from parent nodes. You can only use the "hidden" variable option on variables you create in the expression itself. To remove those unwanted fields, you should use a Field Layout node right after the expression node. It will let you limit the columns you want to have passed out to the next node in the job. You can also rename columns here. Ron

RonAgresta · ‎11-30-2015

You could use an Expression node to do this. Create a new field and use the today() function: date MyDate MyDate = today() Ron

RonAgresta · ‎10-30-2015

Hi, A few tips on this topic: You'll be presented with a dialog when using the SAS Deployment Wizard (SDW) that will configure the SAS Data Remediation Data Server. On this screen, no need to change anything but you'll be asked to provide a password. Use whatever you want for this. Next you'll be asked for an internal SAS Account for SAS Data Remediation Services User. Provide any password you want. This information is created for the Data Management Server jobs for MDM. This identity will be used to make REST web service calls to the Data Remediation API. Later you'll see a dialog that asks for Data Remediation Database User information. You can leave the username as is and again, choose whatever password you would like. This information is used when the Data Remediation application wants to communicate with its database. After providing that information, the SDW installs the Data Remediation database and configures it. It's a Postgres database running on your mid-tier server. You should be able to see it as a new running service when the installation process completes. You don't need to independently set up this database - it's all done for you. Check out the SAS MDM admin guide for additional pre- and post-installation information for SAS MDM. Ron

RonAgresta · ‎10-02-2015

Assuming your Hadoop environment meets the specifications for SAS Data Loader, you don't actually need to ingest data through SAS Data Loader to use its features. SAS Data Loader can work with data that has been put in Hadoop by any tool as long as the data has been registered in Hive. More specifically, you need to have the data layout described in HCatalog in Hive. If you have data in HDFS that has not been described in Hive you can use tools like Hue to describe the data in HDFS. Ron

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