Sorting¶
Since data in CAS can be spread across many machines and may even be redistributed depending on events that occur, the data is not stored in an ordered form. In general, when using statistical actions, this doesn’t make much difference since the CAS actions doing the work will handle the data regardless of the order that it is in. However, when you are bringing a table of data back to the client from CAS using the fetch action, you may want to have it come back in a sorted form.
In [1]: conn = swat.CAS(host, port, username, password)
In [2]: tbl = conn.read_csv('https://raw.githubusercontent.com/'
...: 'sassoftware/sas-viya-programming/master/data/cars.csv')
...:
NOTE: Cloud Analytic Services made the uploaded file available as table TMPWW1WGLQK in caslib CASUSER(kesmit).
NOTE: The table TMPWW1WGLQK has been created in caslib CASUSER(kesmit) from binary data uploaded to Cloud Analytic Services.
In [3]: tbl.fetch(to=5)
Out[3]:
[Fetch]
Selected Rows from Table TMPWW1WGLQK
Make Model Type Origin ... MPG_Highway Weight Wheelbase Length
0 Acura MDX SUV Asia ... 23.0 4451.0 106.0 189.0
1 Acura RSX Type S 2dr Sedan Asia ... 31.0 2778.0 101.0 172.0
2 Acura TSX 4dr Sedan Asia ... 29.0 3230.0 105.0 183.0
3 Acura TL 4dr Sedan Asia ... 28.0 3575.0 108.0 186.0
4 Acura 3.5 RL 4dr Sedan Asia ... 24.0 3880.0 115.0 197.0
[5 rows x 15 columns]
+ Elapsed: 0.00737s, user: 0.005s, sys: 0.001s, mem: 2.02mb
In [4]: tbl.fetch(to=5, sortby=['MSRP'])
Out[4]:
[Fetch]
Selected Rows from Table TMPWW1WGLQK
Make Model Type Origin ... MPG_Highway Weight Wheelbase Length
0 Kia Rio 4dr manual Sedan Asia ... 33.0 2403.0 95.0 167.0
1 Hyundai Accent 2dr hatch Sedan Asia ... 33.0 2255.0 96.0 167.0
2 Toyota Echo 2dr manual Sedan Asia ... 43.0 2035.0 93.0 163.0
3 Saturn Ion1 4dr Sedan USA ... 35.0 2692.0 103.0 185.0
4 Kia Rio 4dr auto Sedan Asia ... 32.0 2458.0 95.0 167.0
[5 rows x 15 columns]
+ Elapsed: 0.0167s, user: 0.011s, sys: 0.005s, mem: 6.78mb
Of course, it is possible to set the direction of the sorting as well.
In [5]: tbl.fetch(to=5, sortby=[{'name':'MSRP', 'order':'descending'}])
Out[5]:
[Fetch]
Selected Rows from Table TMPWW1WGLQK
Make Model Type ... Weight Wheelbase Length
0 Porsche 911 GT2 2dr Sports ... 3131.0 93.0 175.0
1 Mercedes-Benz CL600 2dr Sedan ... 4473.0 114.0 196.0
2 Mercedes-Benz SL600 convertible 2dr Sports ... 4429.0 101.0 179.0
3 Mercedes-Benz SL55 AMG 2dr Sports ... 4235.0 101.0 179.0
4 Mercedes-Benz CL500 2dr Sedan ... 4085.0 114.0 196.0
[5 rows x 15 columns]
+ Elapsed: 0.017s, user: 0.008s, sys: 0.009s, mem: 6.78mb
If you are using the pandas.DataFrame style API for CASTable, you can also use the sort_values() method on CASTable objects.
In [6]: sorttbl = tbl.sort_values(['MSRP'])
In [7]: sorttbl.head()
Out[7]:
Selected Rows from Table TMPWW1WGLQK
Make Model Type Origin ... MPG_Highway Weight Wheelbase Length
0 Kia Rio 4dr manual Sedan Asia ... 33.0 2403.0 95.0 167.0
1 Hyundai Accent 2dr hatch Sedan Asia ... 33.0 2255.0 96.0 167.0
2 Toyota Echo 2dr manual Sedan Asia ... 43.0 2035.0 93.0 163.0
3 Saturn Ion1 4dr Sedan USA ... 35.0 2692.0 103.0 185.0
4 Kia Rio 4dr auto Sedan Asia ... 32.0 2458.0 95.0 167.0
[5 rows x 15 columns]
In [8]: sorttbl = tbl.sort_values(['MSRP'], ascending=False)
In [9]: sorttbl.head()
Out[9]:
Selected Rows from Table TMPWW1WGLQK
Make Model Type ... Weight Wheelbase Length
0 Porsche 911 GT2 2dr Sports ... 3131.0 93.0 175.0
1 Mercedes-Benz CL600 2dr Sedan ... 4473.0 114.0 196.0
2 Mercedes-Benz SL600 convertible 2dr Sports ... 4429.0 101.0 179.0
3 Mercedes-Benz SL55 AMG 2dr Sports ... 4235.0 101.0 179.0
4 Mercedes-Benz CL500 2dr Sedan ... 4085.0 114.0 196.0
[5 rows x 15 columns]
As previously mentioned, this doesn’t affect anything in the table on the CAS server itself, it merely stores away the sort keys and applies them when data is fetched (either through fetch directly, or any method that calls fetch in the background).