Definición y Gestión de Acciones CAS Definidas por el Usuario

Attention : Este código requiere privilegios de administrador.

Este script utiliza `PROC CAS` y el lenguaje CASL para crear un conjunto de acciones personalizadas llamado 'tableSizeHuman'. Este conjunto contiene tres acciones:
1. tableStats: Calcula el tamaño y los detalles de compresión de una tabla CAS (en KB, MB, GB, TB) y proporciona las frecuencias de los tipos de datos de las columnas utilizando `table.tableInfo`, `table.tableDetails`, `table.fetch` con variables calculadas, `table.columnInfo` y `simple.freq`.
2. profCols: Perfila columnas seleccionadas de una tabla CAS a través de la acción `dataDiscovery.profile`.
3. imageMelt: Combina detecciones de procesamiento de imágenes con datos de imágenes recortadas realizando operaciones `transpose.transpose` y una unión `fedsql.execdirect`.
Además, el script crea una nueva CASLIB llamada 'UDAS' que apunta a una ruta específica (`/viyafiles/sasss1/userDefinedActionSets`) y persiste el conjunto de acciones 'tableSizeHuman' en ella como un archivo `.sashdat`, asegurando su disponibilidad para otras sesiones CAS.

Análisis de datos

Type : MIXTE

Las acciones definidas por el usuario procesan tablas CAS existentes cuyos nombres y caslibs se pasan como parámetros (por ejemplo, 'caslib' y 'table'). El script no crea datos de origen brutos, pero genera tablas temporales en CAS para sus cálculos intermedios. La CASLIB 'UDAS' se crea para almacenar las definiciones de las acciones mismas, y no para almacenar datos de entrada en el sentido tradicional. El código comentado sugiere el uso de tablas como 'baseball' que se supone que existen en CAS.

1 Bloque de código

PROC CAS

Explicación :
Este bloque inicializa una sesión CAS y asigna todas las bibliotecas CAS existentes. Luego define un conjunto de acciones CAS personalizadas llamado 'tableSizeHuman' que contiene tres acciones: 'tableStats' para calcular el tamaño de las tablas y las frecuencias de los tipos de datos, 'profCols' para perfilar columnas, e 'imageMelt' para fusionar datos de detección e imágenes. Cada acción utiliza funciones CASL y acciones CAS nativas (`table.tableInfo`, `table.tableDetails`, `table.fetch`, `table.columnInfo`, `simple.freq`, `dataDiscovery.profile`, `transpose.transpose`, `fedsql.execdirect`) para realizar su tarea. Estas acciones están escritas en CASL y se ejecutan dentro de PROC CAS.

¡Copiado!

cas; caslib _all_ assign; /* Orginal code authored by Chris Ricciardi */ /* TB, compressedKB,compressedMB,compressedGB,compressedTB added by Steven Sober */ /* You must modify the path in the CASLIB USDA at the bottom of the code */ proc cas; builtins.defineActionSet / name="tableSizeHuman" actions={ { name="tableStats" desc="Multiple Table actions with calculation of CAS table size and datatype frequency count" parms={ {name="caslib" type="string" required=TRUE} {name="table" type="string" required=TRUE} {name="level" type="string" required=FALSE default="sum"} } definition = " table.tableInfo result=r status=s / caslib=caslib name=table; if 0 != s.severity then do; send_response(s); end; send_response(r); run; table.tableDetails result=r status=s / caslib=caslib name=table level=level; if 0 != s.severity then do; send_response(s); end; send_response(r); run; details = findTable(r); saveresult details caslib=caslib casout='casdatasize' replace; table.fetch result=r status=s / table={caslib=caslib name='casdatasize' computedVars={name='KB',name='MB',name='GB',name='TB', name='compressedKB',name='compressedMB',name='compressedGB',name='compressedTB'} computedVarsProgram=' KB=round(DataSize / (1024),0.01); MB=round(DataSize / (1024*1024),01); GB=round(DataSize / (1024*1024*1024),0.01); TB=round(DataSize / (1024*1024*1024*1024),0.01); compressedKB=round(CompressedSize / (1024),0.01); compressedMB=round(CompressedSize / (1024*1024),0.01); compressedGB=round(CompressedSize / (1024*1024*1024),0.01); compressedTB=round(CompressedSize / (1024*1024*1024*1024),0.01); '} fetchVars={'DataSize', 'VardataSize', 'KB', 'MB', 'GB', 'TB', 'CompressedSize', 'compressedKB', 'compressedMB', 'compressedGB', 'compressedTB'}; if 0 != s.severity then do; send_response(s); end; send_response(r); run; /*size = round((details[1,6] + details[1,7]) / (1024*1024),0.01); print (string)size || 'MB'; run;*/ table.columnInfo result=r status=s / table={caslib=caslib name=table}; if 0 != s.severity then do; send_response(s); end; send_response(r); run; columns = findTable(r); saveresult columns caslib=caslib casout='cascolumns' replace; simple.freq result=r status=s / table={caslib=caslib name='cascolumns'} inputs={{name='type'}}; if 0 != s.severity then do; send_response(s); end; send_response(r); run; " }, { name="profCols" desc="Profile selected columns" parms={ {name="caslib" type="string" required=TRUE} {name="table" type="string" required=TRUE} {name="col" type="string" unkeyedList=TRUE required=TRUE} } definition = " dataDiscovery.profile result=r status=s / table={name=table, caslib=caslib}, casOut={caslib=caslib, name='profcols', replication=0, replace=True}, columns=col, frequencies=2, minmax=2; if 0 != s.severity then do; send_response(s); end; send_response(r); " }, { name="imageMelt" desc="Combine image processing detections with cropped images" parms={ {name="caslib" type="string" required=TRUE} {name="detections" type="string" required=TRUE} {name="cropped" type="string" required=TRUE} {name="casout" type="string" required=TRUE} } definition = " table.columnInfo result=r / table={name=detections caslib=caslib}; col_info = findTable(r); varlist = {}; do colname over col_info; if length(colname.Column) ge 7 then do; obj = substr(colname.Column,1,7); end; if obj = '_Object' then do; tempVar=colname.Column; varlist = varlist + {tempVar}; end; end; run; /*print varlist; run;*/ transpose.transpose / table ={name=detections caslib=caslib groupBy = {'_id_', '_filename_0', '_nObjects_'} computedVars={name='idvalue'} computedVarsProgram='idvalue=""Values""'} casout = {name='obj_melted' caslib=caslib replace=true replication=0} id = {'idvalue'} let = 0 transpose = varlist name = 'ColName'; run; transpose.transpose / table={name='obj_melted' caslib=caslib groupby={'_id_', 'object', '_filename_0', '_nObjects_'} computedVars={{name='object'},{name='type'}} computedVarsProgram=""object=substr(ColName,8,(index(substr(ColName,2),'_')-7)); if type = substr(ColName,(index(substr(ColName,2),'_')+2)) = '' then type = 'objname'; else type = substr(ColName,(index(substr(ColName,2),'_')+2));""} casout={name='obj_melted2' caslib=caslib replace=true replication=0} id={'type'} transpose = {'Values'} let = False; run; table.tableInfo result=r / name=cropped; tinfo = findTable(r); crop = tinfo[1,1]; /*print 'crop is ' crop;*/ clib = tinfo[1,18]; /*print 'clib is ' clib;*/ run; qstring = 'create table ' || clib || '.' || casout || ' {options replace=true replication=0} as select t1.*, t2._filename_0, t2._nObjects_, /*cast(t2.object as double) as object,*/ t2.objname, cast(t2.height as double) as height, cast(t2.width as double) as width, cast(t2.x as double) as x, cast(t2.y as double) as y from ' || clib || '.' || crop || ' t1 left join ' || clib || '.obj_melted2 t2 on (t1._parentId_ = t2._id_ and t1._id_ = cast(t2.object as double))'; /*print qstring;*/ run; fedsql.execdirect / query=qstring; run; table.tableInfo result=r status=s / caslib=caslib name='obj_joined'; if 0 != s.severity then do; send_response(s); end; send_response(r); run; table.dropTable / caslib=caslib name='obj_melted'; run; table.dropTable / caslib=caslib name='obj_melted2'; run; " } } ; run; quit;

1	cas;
2	caslib _all_ assign;
3	/* Orginal code authored by Chris Ricciardi */
4	/* TB, compressedKB,compressedMB,compressedGB,compressedTB added by Steven Sober */
5	/* You must modify the path in the CASLIB USDA at the bottom of the code */
6
7	PROC CAS;
8	BUILTINS.defineActionSet /
9	name="tableSizeHuman"
10	actions={
11	{
12	name="tableStats"
13	desc="Multiple Table actions with calculation of CAS table size and datatype frequency count"
14	parms={
15	{name="caslib" type="string" required=TRUE}
16	{name="table" type="string" required=TRUE}
17	{name="level" type="string" required=FALSE default="sum"}
18	}
19	definition = "
20	table.tableInfo result=r status=s /
21	caslib=caslib
22	name=table;
23	if 0 != s.severity then do;
24	send_response(s);
25	end;
26	send_response(r);
27	run;
28
29	table.tableDetails result=r status=s /
30	caslib=caslib
31	name=table
32	level=level;
33	if 0 != s.severity then do;
34	send_response(s);
35	end;
36	send_response(r);
37	run;
38
39	details = findTable(r);
40	saveresult details caslib=caslib casout='casdatasize' replace;
41
42	table.fetch result=r status=s /
43	table={caslib=caslib name='casdatasize'
44	computedVars={name='KB',name='MB',name='GB',name='TB',
45	name='compressedKB',name='compressedMB',name='compressedGB',name='compressedTB'}
46	computedVarsProgram='
47	KB=round(DataSize / (1024),0.01);
48	MB=round(DataSize / (1024*1024),01);
49	GB=round(DataSize / (102410241024),0.01);
50	TB=round(DataSize / (102410241024*1024),0.01);
51	compressedKB=round(CompressedSize / (1024),0.01);
52	compressedMB=round(CompressedSize / (1024*1024),0.01);
53	compressedGB=round(CompressedSize / (102410241024),0.01);
54	compressedTB=round(CompressedSize / (102410241024*1024),0.01);
55	'}
56	fetchVars={'DataSize', 'VardataSize', 'KB', 'MB', 'GB', 'TB',
57	'CompressedSize', 'compressedKB', 'compressedMB', 'compressedGB', 'compressedTB'};
58
59	if 0 != s.severity then do;
60	send_response(s);
61	end;
62	send_response(r);
63	run;
64
65	/size = round((details[1,6] + details[1,7]) / (10241024),0.01);
66	print (string)size \|\| 'MB';
67	run;*/
68
69	table.columnInfo result=r status=s /
70	table={caslib=caslib name=table};
71	if 0 != s.severity then do;
72	send_response(s);
73	end;
74	send_response(r);
75	run;
76
77	columns = findTable(r);
78	saveresult columns caslib=caslib casout='cascolumns' replace;
79
80	simple.freq result=r status=s /
81	table={caslib=caslib name='cascolumns'}
82	inputs={{name='type'}};
83	if 0 != s.severity then do;
84	send_response(s);
85	end;
86	send_response(r);
87	run;
88	"
89	},
90	{
91	name="profCols"
92	desc="Profile selected columns"
93	parms={
94	{name="caslib" type="string" required=TRUE}
95	{name="table" type="string" required=TRUE}
96	{name="col" type="string" unkeyedList=TRUE required=TRUE}
97	}
98	definition = "
99	dataDiscovery.profile result=r status=s /
100	table={name=table, caslib=caslib},
101	casOut={caslib=caslib, name='profcols', replication=0, replace=True},
102	columns=col,
103	frequencies=2,
104	minmax=2;
105	if 0 != s.severity then do;
106	send_response(s);
107	end;
108	send_response(r);
109	"
110	},
111	{
112	name="imageMelt"
113	desc="Combine image processing detections with cropped images"
114	parms={
115	{name="caslib" type="string" required=TRUE}
116	{name="detections" type="string" required=TRUE}
117	{name="cropped" type="string" required=TRUE}
118	{name="casout" type="string" required=TRUE}
119	}
120	definition = "
121	table.columnInfo result=r /
122	table={name=detections caslib=caslib};
123	col_info = findTable(r);
124	varlist = {};
125	do colname over col_info;
126	if length(colname.Column) ge 7 then do;
127	obj = substr(colname.Column,1,7);
128	end;
129	if obj = '_Object' then do;
130	tempVar=colname.Column;
131	varlist = varlist + {tempVar};
132	end;
133	end;
134	run;
135
136	/*print varlist;
137	run;*/
138
139	transpose.transpose / table ={name=detections caslib=caslib groupBy = {'_id_', '_filename_0', '_nObjects_'}
140	computedVars={name='idvalue'}
141	computedVarsProgram='idvalue=""Values""'}
142	casout = {name='obj_melted' caslib=caslib replace=true replication=0}
143	id = {'idvalue'}
144	let = 0
145	transpose = varlist
146	name = 'ColName';
147	run;
148
149	transpose.transpose / table={name='obj_melted' caslib=caslib groupby={'_id_', 'object', '_filename_0', '_nObjects_'}
150	computedVars={{name='object'},{name='type'}}
151	computedVarsProgram=""object=substr(ColName,8,(index(substr(ColName,2),'_')-7));
152	if type = substr(ColName,(index(substr(ColName,2),'_')+2)) = ''
153	then type = 'objname';
154	else type = substr(ColName,(index(substr(ColName,2),'_')+2));""}
155	casout={name='obj_melted2' caslib=caslib replace=true replication=0}
156	id={'type'}
157	transpose = {'Values'}
158	let = False;
159	run;
160
161	table.tableInfo result=r /
162	name=cropped;
163	tinfo = findTable(r);
164	crop = tinfo[1,1];
165	/print 'crop is ' crop;/
166	clib = tinfo[1,18];
167	/print 'clib is ' clib;/
168	run;
169
170	qstring = 'create TABLE ' \|\| clib \|\| '.' \|\| casout \|\| ' {options replace=true replication=0} as select
171	t1., t2._filename_0, t2._nObjects_, /cast(t2.object as double) as object,*/ t2.objname,
172	cast(t2.height as double) as height, cast(t2.width as double) as width,
173	cast(t2.x as double) as x, cast(t2.y as double) as y
174	from ' \|\| clib \|\| '.' \|\| crop \|\| ' t1 left join ' \|\| clib \|\| '.obj_melted2 t2
175	on (t1._parentId_ = t2._id_ and t1._id_ = cast(t2.object as double))';
176	/print qstring;/
177	run;
178
179	fedsql.execdirect /
180	query=qstring;
181	run;
182
183	table.tableInfo result=r status=s /
184	caslib=caslib
185	name='obj_joined';
186	if 0 != s.severity then do;
187	send_response(s);
188	end;
189	send_response(r);
190	run;
191
192	table.dropTable / caslib=caslib name='obj_melted';
193	run;
194	table.dropTable / caslib=caslib name='obj_melted2';
195	run;
196	"
197	}
198	}
199	;
200	RUN;
201	QUIT;

2 Bloque de código

PROC CAS Data

Explicación :
Este bloque agrega una nueva biblioteca CAS (CASLIB) llamada 'UDAS' que apunta a una ruta de sistema específica (`/viyafiles/sasss1/userDefinedActionSets`). El objetivo de esta CASLIB es almacenar archivos persistentes para las acciones definidas por el usuario. Luego, utiliza la acción `builtins.actionSetToTable` para convertir el conjunto de acciones 'tableSizeHuman' definido previamente en una tabla CAS persistente en la CASLIB 'UDAS'. Finalmente, la acción `table.save` se utiliza para guardar esta tabla CAS como un archivo `tableSizeHuman.sashdat` en el controlador CAS, haciendo que el conjunto de acciones definido por el usuario esté disponible para futuras sesiones CAS.

¡Copiado!

1	PROC CAS;
2	TABLE.addCaslib /
3	caslib='UDAS'
4	dataSource={srctype='path'}
5	path="/viyafiles/sasss1/userDefinedActionSets";
6	RUN;
7	QUIT;
8
9	PROC CAS;
10	BUILTINS.actionSetToTable /
11	actionSet="tableSizeHuman"
12	casOut={caslib="UDAS" name="tableSizeHuman" replace=True};
13	RUN;
14	TABLE.save /
15	caslib="UDAS"
16	TABLE="tableSizeHuman"
17	name="tableSizeHuman.sashdat"
18	replace=True;
19	QUIT;

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