PhixFlow generates processing statistics which are saved to the database. into a database table.
These statics are for use by administrators and designers who are tuning for performance.
See System Configuration for how to enable and manage stats generation.
Contents
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Statistics Table Structure
The following Processing statistics are currently recorded and available as data records in the STATS table. (See STATS record definition)
Activity Statistics
Activity Statistics are recorded from TaskPlans executed, Actions triggered.
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TaskPlan/Action ID
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{Number of tasks started in this timeslot. The timeslot is set in the System Configuration > System Tuning Tab
Stats DB Logging Seconds field}
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TaskPlan/Action ID
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Stats DB Logging Seconds field}
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TaskPlan/Action ID
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TaskPlan/Action ID
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Stats DB Logging Seconds field}
Stream Statistics
This is a record of data volumes written to Streams and Exporters
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TaskPlan/Action ID
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TaskPlan/Action ID
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TaskPlan/Action ID
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insertVolumeBytes
(bytes)
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TaskPlan/Action ID
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insertTimeTotal
(seconds)
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TaskPlan/Action ID
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TaskPlan/Action ID
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TaskPlan/Action ID
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updateVolumeBytes
(bytes)
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TaskPlan/Action ID
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updateTimeTotal
(seconds)
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The timeslot is set in the System Configuration > System Tuning Tab
Stats DB Logging Seconds field
Pipe Statistics
This is a record of Pipe Read Statistics
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TaskPlan/Action ID
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TaskPlan/Action ID
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readTime
(seconds)
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TaskPlan/Action ID
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readTimeMax
(seconds)
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TaskPlan/Action ID
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This is a record of Pipe Queue Statistics
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TaskPlan/Action ID
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sumEnqueueTime
(seconds)
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TaskPlan/Action ID
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TaskPlan/Action ID
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sumDequeueTime
(seconds)
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TaskPlan/Action ID
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This is a record of Pipe Lookup Statistics
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TaskPlan/Action ID
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TaskPlan/Action ID
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TaskPlan/Action ID
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TaskPlan/Action ID
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TaskPlan/Action ID
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TaskPlan/Action ID
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Database Statistics Record Structure
The table structure for STATS is as follows:
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Statistics Type:
E.g. 'Activity, Pipe, PipeLookup, PipeQueue, Stream'
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The object initiating the activity - eg. "TaskPlan", or "Action"
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The name of the initiating TaskPlan or Action / other object.
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e.g. The "Streams" ID that Analysis was run on.
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This a dotted notation indicating the full context.
eg. TaskPlan1.Stream X.in
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generated in a single table, stats.
The table structure for stats is as follows:
Column | Type | Description |
|---|---|---|
| from_dtm | Datetime | The start time of the period that this measure refers to |
| to_dtm | Datetime | The end time of the period that this measure refers to |
| initiator_type | String | The high-level object initiating the activity - eg. "TaskPlan", or "Action" |
| initiator_id | Id (String) | The ID of the initiating TaskPlan or Action / other object. |
| initiator_name | String | The name of the initiating object. |
| context_type | String | The activity triggered by the initiator. eg "Stream" |
| context_id | Id (String) | e.g. The "Streams" ID that Analysis was run on. |
| context_name | String | eg. The name of the stream that Analysis was run on.` |
| full_context | String | This a dotted notation indicating the full context. eg. TaskPlan1.StreamX.in |
| stats_type | String | The aspect of the system's behaviour that is measured |
| data_type | String | The units of the measurement |
| data_value | Double | The value of the measurement |
Statistics Dimensions
The performance statistics are classified by 4 major dimensions:
Initiator
the high-level object initiating the system activity e.g. Task Plan
Context
the low-level object with which the system activity is associated e.g. Pipe
Stats Type
the aspect of system behaviour being measured e.g. database read times
Sample DateTime
Aggregate values apply to a period between a start and end time. Spot values apply to the end time.
Initiator
The initiator is the object representing the user activity that caused the system activity.
Initiators include
- (Running an) Action
- (Running a) Task Plan
- (Running a) Stream
- (Viewing data for a) Stream View
- System, for internal activities and things that can't be allocated to any specific cause e.g. memory and CPU usage.
Where one initiator could include another, the activity is recorded against the initiator closest to the user
e.g. the user runs an Action which runs a Task Plan - the initiator is the Action.
e.g. the user runs the same Task Plan directly - the initiator is the Task Plan
With the exception of System, the initiator is identified by name, type and id.
Context
The context is the most detailed object to which the activity can be attributed.
Contexts include
- Stream Action
- Task Plan
- Stream
- Pipe
- File / Database / Http Collector
- File / Database / Http Exporter
- System
With the exception of System, the context is identified by name, full name, type and id.
The full name is a dot-separated list of objects from the highest level to the lowest, ending in the context object.
Stats Type / Data Type
Stats Type is the specific aspect of system behaviour being measured.
Data Type
Data Type contains the units of the measurement.
Data types that represent a snapshot value are shown as the plural unit e.g. the Data Type for the amount of Java memory used is 'bytes'.
Data Types that represent a rate, or amount of throughput are shown as the average rate per second e.g. the data type for the number of items generated in a stream is 'items/s' i.e. items per second. The value is calculated by dividing the total number or amount recorded in the sampling period by the duration of the sampling period in seconds. The rate per second is shown rather than the absolute number so that if the sampling period is changed, the numbers (the rate per second) stay in the same range.
Data Types include
| Data Type | Description |
|---|---|
| activities/s | Activities per second |
| seconds | A simple time value, e.g. a maximum wait time for a database statement to execute |
| seconds/s | Seconds per second. Stats that record times cumulative times (e.g. the total of internal wait times) are normalised per second. Where this applies to a single-threaded stats type, the value will always be between 0.0 and 1.0, where a value near 1.0 means that that part of the system is waiting nearly 100% of the time. |
| items | A number of items (records), e.g. the number of items in a pipe cache. |
| items/s | The number of items processed per second e.g. the number of items generated per second. |
| ops/s | A number of operations per second (e.g. databaes reads) |
| bytes | A total number of bytes, e.g. the number of bytes of Java memory used. |
| busy | The fraction of the time that a resource is busy e.g. the CPU utilisation. |
| tasks | A number of tasks |
Stats Type
Each Stats Types record a single type of data. The data type is stored in the data as an indicator of the units of the data value for each stats type.
Activity
Activity stats record information about the high-level activities that the system was performing at any time. In general these are user-level actions e.g. running a Task Plan.
| Stats Type | Data Type | Description |
|---|---|---|
| activity.start | activities/s | The number of activities per second that started |
| activity.end | activities/s | The number of activities per second that finished |
| activity.time | seconds/s | The time spent per second running the activities |
Database
Database stats record aggregate values for low-level database operations.
| Stats Type | Data Type | Description |
|---|---|---|
| data.exec.time | seconds/s | Time spent executing database statements. |
| data.read.time | seconds/s | Time spent reading from a database. |
| data.read.ops | ops/s | Number of database read operations per second |
| data.read.items | items/s | Number of items (records) read from database per second |
| data.write.time | seconds/s | Time spent writing to a database. |
| data.write.ops | ops/s | Number of database write operations per second |
| data.write.items | items/s | Number of items (records) written to database per second |
Data Generation
Data Generation stats record details of stream data generation.
| Stats Type | Data Type | Description |
|---|---|---|
| csf.create.time | seconds/s | Time spent creating candidate sets |
| csf.find.time | seconds/s | Time spent finding data for candidate sets |
| csf.process.time | seconds/s | Time spent processing candidate sets to create stream items. |
| generate.time | items/s | Number of items generated per second |
| generate.items | seconds/s | Time spent per second generating items |
Data Output
These stats record details of the output phase of Data Generation, in which items are written to an output queue so that they can be written out by one or more asynchronous writer processes.
| Stats Type | Data Type | Description |
|---|---|---|
| output.enqueue.time | seconds/s | Time spent adding generated items to the output queue |
| output.dequeue.time | seconds/s | Time spent taking generated items from the output queue |
| output.dequeue.items | items/s | The number of items/s taken from the output queue |
| output.wait.time | seconds/s | Time spent waiting for the output writer |
| output.write.time | seconds/s | Time spent writing out items |
| output.write.items | items/s | The number of items written out / second |
| output.reject.items | items/s | The number of items rejected / second |
Pipes (Pull)
These stats types record various aspects of the behaviour of pull pipes
| Stats Type | Data Type | Description |
|---|---|---|
| pipe.pull.idle.time | seconds/s | Time spent idle |
| pipe.pull.prepare.time | seconds/s | Time spent preparing (creating pipe candidate sets) |
| pipe.pull.prepared.time | seconds/s | Time spent after preparation |
| pipe.pull.process.time | seconds/s | Time spent creating candidate sets |
| pipe.pull.processed.time | seconds/s | Time spent after processing |
| pipe.pull.read.time | seconds/s | Time spent reading |
| pipe.pull.readresponse.time | seconds/s | Time spent processing read responses |
| pipe.pull.submitted.time | seconds/s | Time spent submitting read requests |
Pipes (Lookups)
These stats types record various aspects of the behaviour of lookup pipes.
| Stats Type | Data Type | Description |
|---|---|---|
| lookup.added.items | items/s | The number of items added to a pipe cache per second |
| lookup.clash.ops | ops | The number of lookups where another process was reading data for the same lookup |
| lookup.miss.ops | ops/s | The number of lookups per second not satisfied by data already in the pipe cache |
| lookup.removed.items | items/s | The number of items removed from a pipe cache per second |
| lookup.size.items | items | The number of items in a pipe cache |
| pipe.lookup.ops | ops/s | The number of lookups / second |
| pipe.lookup.time | seconds/s | The time spent doing lookups / second |
System Performance
System stats record aspects of system behaviour.
| Stats Type | Data Type | Description |
|---|---|---|
| java.memory.free | bytes | The amount of java memory that is free |
| java.memory.used | bytes | The amount of java memory that is used |
| java.memory.total | bytes | The total amount of java memory |
| system.cpu | busy | The fraction of the time that the cpu is busy |
Work Queues
PhixFlow maintains a number of queues for asynchronous task work / task processing.
These statistics record the occupancy levels of these queues, comprising for each queue the number of tasks queued (waiting) + the number running.
| Stats Type | Data Type | Description |
|---|---|---|
| workqueue.cspt.size | tasks | The number of tasks in the CSPT work queue |
| workqueue.dgr.size | tasks | The number of tasks in the DGR work queue |
| workqueue.pdp.size | tasks | The number of tasks in the PDP work queue |
| workqueue.prepare.size | tasks | The number of tasks in the PREPARE work queue |
| workqueue.read.size | tasks | The number of tasks in the READ work queue |
| workqueue.write.size | tasks | The number of tasks in the WRITE work queue |
| workqueue.other.size | tasks | The number of tasks in the OTHER work queue |
| workqueue.export.size | tasks | The number of tasks in the EXPORT work queue |
| workqueue.view.size | tasks | The number of tasks in the VIEW work queue |
Examples
These are examples of extracting specific sub-sets of the stats data.
These examples show the use of direct sql statements to extract useful sub-sets of the stats data, but you could also import all data into a Stream and analyse it there.
Monitoring Memory Usage
E.g. to extract Java memory total and free:
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select *
from stats
where stats_type in ('java.memory.free', 'java.memory.total')
order by to_dtm; |
Monitoring Pipe Cache Sizes
E.g. to extract all pipe caches over a certain size:
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select *
from stats
where stats_type = 'lookup.size.items' and data_value>1000000
order by full_context, to_dtm; |