Table 42. Usage Tracking Data
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USER_NAME |
The name of the user who submitted the query. |
REPOSITORY_NAME |
The name of the repository the query accesses. |
SUBJECT_AREA_NAME |
The name of the business model being accessed. |
NODE_ID |
Reserved for future use |
START_TS |
The date and time the logical query was submitted. |
START_DT |
The date the logical query was submitted. |
START_HOUR_MIN |
The hour and minute the logical query was submitted. |
END_TS |
The date and time the logical query finished. The start and end timestamps also reflect any time the query spent waiting for resources to become available. |
END_DT |
The date the logical query was completed. |
END_HOUR_MIN |
The hour and minute the logical query was completed. |
QUERY_TEXT |
The SQL submitted for the query. |
SUCCESS_FLG |
The completion status of the query: 0 - The query completed successfully with no errors. 1 - The query timed out. 2 - The query failed because row limits were exceeded. 3 - The query failed due to some other reason. |
ROW_COUNT |
The number of rows returned to the query client. |
COMPILE_TIME_SEC |
The time in seconds required to compile the query |
TOTAL_TIME_SEC |
The time in seconds that the Siebel Analytics Server spent working on the query while the client waited for responses to its query requests. |
NUM_DB_QUERY |
The number of queries submitted to back-end databases in order to satisfy the logical query request. For successful queries (SuccessFlag = 0) this number will be 1 or greater. |
CUM_DB_TIME_SEC |
The total amount of time in seconds that the Siebel Analytics Server waited for back-end physical databases on behalf of a logical query. |
CUM_NUM_DB_ROW |
The total number of rows returned by the back-end databases. |
CACHE_IND_FLG |
Y indicates a cache hit for the query, N indicates a cache miss. |
QUERY_SRC_CD |
The source of the request, e.g., Drill or Report. |
SAW_SRC_PATH |
The path name within the Analytics web catalog for the request. |
SAW_DASHBOARD |
The name of the dashboard. Null if the query was not submitted via an Analytics dashboard. |