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I am having an issue where I am trying to create a volatile table using SAS, then being able to connect and review this table. Ultimately I am trying to join a Teradata Volatile table with Hadoop data, but I figure this is the first step. You can see a sample layout of my code below, and the only error I get when running is that my_VTD_Test doesn't exist, which is true at the start of the program. Everything else completes just fine, but when I try to look at the table data, I get an error that it doesn't exist again. So it looks like its running but not gathering any data. I appreciate any feedback with this.
libname tdwork teradata AUTHDOMAIN=MYAUTH
mode=teradata server="myserver"
connection=global dbmstemp=yes;
PROC SQL NOERRORSTOP;
CONNECT TO TERADATA (AUTHDOMAIN=TDAUTH server="myserver" connection=global mode=teradata);
execute (drop table my_VTD_Test) BY Teradata;
execute( create volatile table my_VTD_Test as
(select Name, Place, Service
from MYTDSCHEMA.Table_NAME
)
with data primary index(Name) On Commit Preserve Rows ) by teradata;
DISCONNECT FROM teradata;
quit;
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There have been quite a few spam questions over the past few months where it took sometimes days until they got removed.
Proposal
Implement an automated process that moves questions from the visible list to some hidden queue for investigation if marked by multiple users an inappropriate content.
To avoid that this process can get misused: Only include users that marked the question if they are not New Users but already on a certain level (to exclude fake users).
And just thinking:
Eventually request from New Users for their first few post some additional identification step when posting a question to make it a bit harder to automate posting such questions.
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How do I get more detail about the lines in BOLD? When I use option LISTOBS it will list the observations that it finds different. However when I view them I don't see any differences. How do I find out which vars are different when there are 95 vars? (Method=RELATIVE(0.0000222), Criterion=1.0E-09) Data Set Summary Dataset Created Modified NVar NObs ORDATA.ORACLETEMP 03MAY24:07:20:37 03MAY24:07:20:37 95 26553 SNOWDATA.SNOWTEMP 03MAY24:07:21:21 03MAY24:07:21:21 95 26553 Variables Summary Number of Variables in Common: 95. Number of ID Variables: 10. Number of Observations in Common: 24450. Number of Observations in ORDATA.ORACLETEMP but not in SNOWDATA.SNOWTEMP: 2103. Number of Observations in SNOWDATA.SNOWTEMP but not in ORDATA.ORACLETEMP: 2103. Total Number of Observations Read from ORDATA.ORACLETEMP: 26553. Total Number of Observations Read from SNOWDATA.SNOWTEMP: 26553. Number of Observations with Some Compared Variables Unequal: 0. Number of Observations with All Compared Variables Equal: 24450. Values Comparison Summary Number of Variables Compared with All Observations Equal: 85. Number of Variables Compared with Some Observations Unequal: 0. Total Number of Values which Compare Unequal: 0. Total Number of Values not EXACTLY Equal: 3628. Maximum Difference Criterion Value: 2.2094E-16. Here is my code: title "ordata.&ordsn versus &snowdsn"; proc compare base=ordata.&ordsn compare=snowdata.&snowdsn Criterion=0.000000001 fuzz=.001 out=result listobs outbase outcomp outdif outnoequal maxprint=50; id member medicaid_no claim_number line_number PAY_DT F_DOS L_DOS DOS AMT_REQ QTY ; attrib _all_ label=''; format _all_; informat _all_; run;
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I tried ("cou" is 1,2,3,4,5.....; "var" is continuous variable with decimal points):
proc sql;
create table mt as
select cou,
pctl(75, var) as var_p75
from check_1
group by cou;
quit;
But it returns me with multiple rows per cou.
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Hi,
I need some help with writing a SAS code to handle the following scenario.
I have a data set that has multiple sites; each site has multiple patients; and each patient can have data of up to 7 days (one row represents one day). The data set has form start and save time. Data set is also setup to have no duplicates. First day data of each patient should always have the previous save and open time (both are user defined variables) as NULL. e.g., sr.1, 8, and 9 will have previous open and save time variables as NULL. And using these variables, I want to calculate the the following for each patient at a site:
number of hours a patient took between today's and yesterday's start times (i.e., from today's start to previous start) and
number of hours a patient took between today's open and yesterday's start times (i.e., from today's start to previous day save)
Sr.
PT
SITE
START_TIME
SAVE_TIME
1
001
01
4/9/2024 16:44
4/9/2024 16:46
2
001
01
4/10/2024 16:39
4/10/2024 16:40
3
001
01
4/11/2024 16:07
4/11/2024 16:08
4
001
01
4/12/2024 16:05
4/12/2024 16:06
5
001
01
4/13/2024 20:05
4/13/2024 20:06
6
001
01
4/14/2024 19:31
4/14/2024 19:52
7
001
01
4/15/2024 16:25
4/15/2024 16:25
8
002
01
4/15/2024 16:19
4/15/2024 16:20
9
003
01
4/15/2024 16:21
4/15/2024 16:22
10
002
02
4/3/2024 18:34
4/3/2024 18:41
11
002
02
4/4/2024 18:03
4/4/2024 18:09
12
002
02
4/6/2024 21:11
4/6/2024 21:14
13
002
02
4/6/2024 21:14
4/6/2024 21:16
14
002
02
4/7/2024 18:17
4/7/2024 18:20
15
002
02
4/8/2024 18:12
4/8/2024 18:14
16
002
02
4/9/2024 18:06
4/9/2024 18:08
17
004
02
4/5/2024 18:03
4/5/2024 18:10
18
004
02
4/6/2024 16:27
4/6/2024 16:32
19
004
02
4/7/2024 19:18
4/7/2024 19:22
20
004
02
4/8/2024 18:01
4/8/2024 18:07
21
004
02
4/9/2024 18:06
4/9/2024 18:16
22
004
02
4/10/2024 18:08
4/10/2024 18:10
23
004
02
4/11/2024 19:22
4/11/2024 19:26
24
005
02
4/8/2024 18:05
4/8/2024 18:07
25
005
02
4/9/2024 19:32
4/9/2024 19:34
26
005
02
4/10/2024 18:45
4/10/2024 18:47
27
005
02
4/11/2024 18:02
4/11/2024 18:04
28
005
02
4/12/2024 18:04
4/12/2024 18:07
29
005
02
4/13/2024 18:01
4/13/2024 18:03
30
005
02
4/14/2024 18:06
4/14/2024 18:08
Thanks so much in advance for all the help.
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