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CAS Joins with Deep Learning and Search Analytics

cas; caslib _all_ assign;

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CAS Joins with Deep Learning and Search Analytics

options caslib=casuser;

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Example of GROUPBY aggregation with CASL and FedSQL

/* CAS Enabled */ /* CASL GROUPBY Action Example */ /* LIBNAME using the CAS engine */ libname CASWORK cas caslib=casuser; /* Changing the default location of all one level named tables */ /* from SASWORK to CASWORK */ options USER = CASWORK; %put &_sessref_; caslib _all_ assign;

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Example of GROUPBY aggregation with CASL and FedSQL

options caslib="casuser"; proc fedsql sessref=casauto; create table baseball_groupby as (select sum(nhits) as nhits_sum from baseball group by div, team) ; quit;

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Frequency Analysis with PROC FREQTAB and CAS

cas; %put &_sessref_; caslib _all_ assign; data casuser.baseball; set sashelp.baseball; run; options sessopts=(metrics=true);

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Parallel Execution of CAS Regressions with SAS/CONNECT

rsubmit session1 wait=no; options casdatalimit=10G; options compress=yes; cas host="19w47mpp-2.gtp-americas.sashq-d.openstack.sas.com" port=5570 sessopts=(TIMEOUT=99,DQLOCALE=ENUSA); caslib _all_ assign; data casuser.cars; set sashelp.cars; run;

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Parallel Execution of CAS Regressions with SAS/CONNECT

proc cas; session casauto; simple.regression result=reg status=rc / alpha=0.05, order=3, target="mpg_highway", inputs={"weight"}, table={caslib="casuser", name="cars"}; run; if (rc.severity == 0) then do; saveresult reg casout="reg1"; table.fetch / ...

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Parallel Execution of CAS Regressions with SAS/CONNECT

rsubmit session2 wait=no; options casdatalimit=10G; options compress=yes; cas host="19w47mpp-2.gtp-americas.sashq-d.openstack.sas.com" port=5570 sessopts=(TIMEOUT=99,DQLOCALE=ENUSA); caslib _all_ assign; data casuser.cars; set sashelp.cars; run;

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Parallel Execution of CAS Regressions with SAS/CONNECT

proc cas; session casauto; simple.regression result=reg2 status=rc / alpha=0.15, order=2, target="mpg_highway", inputs={"weight"}, table={caslib="casuser", name="cars"}; run; if (rc.severity == 0) then do; saveresult reg2 casout="reg2"; table.fetch /...

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Training a Gradient Boosting Model for Salary Prediction

cas; caslib _all_ assign; data casuser.baseball; set sashelp.baseball; run;