This is the column description of each data column of WI_JOBSLOTUSAGEBYGROUPDAILY and how each column is filled with data.
Column Name |
Description |
Key |
CLUSTER_CODE |
This comes from the CLUSTER_CODE field in the hourly table. |
Primary key |
TIME_STAMP |
This is in GMT and is always end in the day. The record is aggregated in a localized day. After the aggregation, the time_stamp is then transformed back at GMT and stored in this field. Thus, this time_stamp always in the GMT form of the localized day in midnight. |
Primary key |
GROUP_TYPE |
This indicates what kind of grouping this record belongs to. The different group type are: "By Host", "By Jobname", "By JobGroup", "By Project", "By Queue", "By User", "By UserGroup" and "By Cluster". |
Primary key |
GROUP_CODE |
This could comes from different source and it is depends on the group_type. If the group_type is "By Host", then it is one of the host name that comes from a subfield in the "Exechostlist" from the data file. The subfield contains the hostname and is being used here. If it is "By JobName", then it comes from the "JobName" field. If it is "By Project", then it comes from the "ProjectName". If it is "By Queue", then it comes from the "QueueName". If it is "By User", then it comes from the "UserName". If it is "By UserGroup", then it comes from the "UserGroupName". If it is "By Cluster", then it comes from the "ClusterName". Once we get the name, we then look it up in the wi_dimensioncode table to see if we have already has a record of it in there by matching the dimension_name. If we do, then we'll get the code back, otherwise, we will insert it into the wi_dimensioncode table and generate the code. The code itself is a positive integer and each new code is equal to the maximum of the existing code+1. |
Primary key |
MIN_SLOT_USAGE |
If the "GroupBy" is "By Host", then for each host, we calculate the slot usage as describe in the beginning of this page. Then, we aggregate them together based on the same "Cluster", "GroupBy", "TimeDiff" and "HostCode". For the others, we just group by "Cluster", "GroupBy", "TimeDiff" and "GroupCode" and the usage comes from the "Slot" field in the data file. We find the minimum of the slot usage for the day and put it into this field. |
|
MAX_SLOT_USAGE |
If the "GroupBy" is "By Host", then for each host, we calculate the slot usage as describe in the beginning of this page. Then, we aggregate them together based on the same "Cluster", "GroupBy", "TimeDiff" and "HostCode". For the others, we just group by "Cluster", "GroupBy", "TimeDiff" and "GroupCode" and the usage comes from the "Slot" field in the data file. We find the maximum of the slot usage for the day and put it into this field. |
|
TOTAL_SLOT_USAGE |
If the "GroupBy" is "By Host", then for each host, we calculate the slot usage as describe in the beginning of this page. Then, we aggregate them together based on the same "Cluster", "GroupBy", "TimeDiff" and "HostCode". For the others, we just group by "Cluster", "GroupBy", "TimeDiff" and "GroupCode" and the usage comes from the "Slot" field in the data file. We find the sum of the slot usage for the day and put it into this field. |
|
COUNTER |
This is the number of records being aggregated for the day for the slot usage calculation. The records itself is first aggregated across the same interval before aggregated again for the day. |
|
MIN_SLOT_UTIL |
If the "GroupBy" is "By Host", then for each host, we calculate the slot utilization as describe in the beginning of this page. Then, we aggregate them together based on the same "Cluster", "GroupBy", "TimeDiff" and "HostCode". For the "By Queue", we just group by "Cluster", "GroupBy", "TimeDiff" and "GroupCode" and the usage comes from the "Slot" field in the data file. We find the minimum of the slot utilization for the day and put it into this field. For the other "GroupBy", we will not calculate utilization and will not insert any value into this field. |
|
MAX_SLOT_UTIL |
If the "GroupBy" is "By Host", then for each host, we calculate the slot utilization as describe in the beginning of this page. Then, we aggregate them together based on the same "Cluster", "GroupBy", "TimeDiff" and "HostCode". For the "By Queue", we just group by "Cluster", "GroupBy", "TimeDiff" and "GroupCode" and the usage comes from the "Slot" field in the data file. We find the maximum of the slot utilization for the day and put it into this field. For the other "GroupBy", we will not calculate utilization and will not insert any value into this field. |
|
AVG_SLOT_UTIL |
If the "GroupBy" is "By Host", then for each host, we calculate the slot utilization as describe in the beginning of this page. Then, we aggregate them together based on the same "Cluster", "GroupBy", "TimeDiff" and "HostCode". For the "By Queue", we just group by "Cluster", "GroupBy", "TimeDiff" and "GroupCode" and the usage comes from the "Slot" field in the data file. We calculate the average of the slot utilization for each interval and then average them across the day. For the other "GroupBy", we will not calculate utilization and will not insert any value into this field. |
|
COUNTER_UTIL |
This is the number of records being aggregated for the day for the slot usage calculation. The records itself is first aggregated across the same interval before aggregated again for the day. If the Min_slot_util is equal to -1 (meaning no slot utilization), then this will be zero. For the other "GroupBy", we will not calculate utilization and will not insert any value into this field. |
|
CORE_HOUR |
The core hour is resulted from a mapping of the original time_stamp in local time. If the time_stamp is within the range from Monday to Friday, 9am to 5pm, then the core_hour will be 1, otherwise it will be 0. |
Primary key |
INSERT_SEQ |
This is a system generated sequence number. For each new record inserted, an unique sequence number is being assigned to this column. |
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