getStreamEngineStat
Syntax
getStreamEngineStat()
Alias: getAggregatorStat
Arguments
None
Details
Return a dictionary of tables with various metrics about all stream engines.
-
Table TimeSeriesEngine returns the following columns about time-series engines:
Column Name Description name name of the stream engine user name of the user who created the stream engine status status of the stream engine. "OK" means available; "FATAL" means unavailable lastErrMsg the latest error message windowTime the length of the data window step the duration between 2 adjacent calculations useSystemTime whether the stream engine is triggered as soon as data are injected into the system garbageSize the threshold of the number of records in memory that triggers memory cleaning numGroups the number of groups that the stream engine has handled numRows the number of records that has entered the stream engine numMetrics the number of metrics calculated by the stream engine metrics the metacode of the metrics calculated by the stream engine memoryUsed the amount of memory used snapshotDir the directory to save engine snapshot snapshotInterval the interval to save snapshot snapshotMsgId the msgId of engine snapshot snapshotTimestamp the timestamp of snapshot -
Table CrossSectionalEngine returns the following columns about cross-sectional engines:
Column Name Description name name of the stream engine user name of the user who created the stream engine status status of the stream engine. "OK" means available; "FATAL" means unavailable lastErrMsg the latest error message numRows the number of records that has entered the stream engine numMetrics the number of metrics calculated by the stream engine metrics the metacode of the metrics calculated by the stream engine triggeringPattern how calculations are triggered triggeringInterval the duration in milliseconds between 2 adjacent calculations memoryUsed the amount of memory used -
Table AnomalyDetectionEngine returns the following columns about the anomaly detection engines:
Column Name Description name name of the stream engine user name of the user who created the stream engine status status of the stream engine. "OK" means available; "FATAL" means unavailable lastErrMsg the latest error message numGroups the number of groups that the stream engine has handled numRows the number of records that has entered the stream engine numMetrics the number of metrics calculated by the stream engine metrics the metacode of the metrics calculated by the stream engine snapshotDir the directory to save engine snapshot snapshotInterval the interval to save snapshot snapshotMsgId the msgId of engine snapshot snapshotTimestamp the timestamp of snapshot garbageSize the threshold of the number of records in memory that triggers memory cleaning memoryUsed the amount of memory used -
Table ReactiveStateEngine returns the following columns about the reactive state engines:
Column Name Description name name of the stream engine user name of the user who created the stream engine status status of the stream engine. "OK" means available; "FATAL" means unavailable lastErrMsg the latest error message numGroups the number of groups that the stream engine has handled numRows the number of records that has entered the stream engine numMetrics the number of metrics calculated by the stream engine memoryUsed the amount of memory used snapshotDir the directory to save engine snapshot snapshotInterval the interval to save snapshot snapshotMsgId the msgId of engine snapshot snapshotTimestamp the timestamp of snapshot -
Table SessionWindowEngine returns the following columns about the session window engine:
Column Name Description name name of the stream engine user name of the user who created the stream engine status status of the stream engine. "OK" means available; "FATAL" means unavailable lastErrMsg the latest error message sessionGap gap between 2 session windows useSystemTime whether the stream engine is triggered as soon as data are ingested into the system numGroups the number of groups that the stream engine has handled numRows the number of records that has entered the stream engine numMetrics the number of metrics calculated by the stream engine Metrics the metacode of the metrics calculated by the stream engine memoryUsed the amount of memory used snapshotDir the directory to save snapshot snapshotInterval the interval to save snapshot snapshotMsgId the message ID (msgId) of engine snapshot snapshotTimestamp the timestamp of snapshot -
Table DailyTimeSeriesEngine returns the following columns about the daily time series engine:
Column Name Description name name of the stream engine user name of the user who created the stream engine status status of the stream engine. "OK" means available; "FATAL" means unavailable lastErrMsg the latest error message windowTime the length of the window step the duration between 2 adjacent calculations useSystemTime whether the stream engine is triggered as soon as data are injected into the system garbageSize the threshold of the number of records in memory that triggers memory cleaning numGroups the number of groups that the stream engine has handled numRows the number of records that has entered the stream engine numMetrics the number of metrics calculated by the stream engine metrics the metacode of the metrics calculated by the stream engine memoryUsed the amount of memory used snapshotDir the directory to save snapshot snapshotInterval the interval to save snapshot snapshotMsgId the message ID (msgId) of engine snapshot snapshotTimestamp the timestamp of snapshot -
Table AsofJoinEngine returns the following columns about the as of join engine:
Column Name Description name name of the stream engine user name of the user who created the stream engine status status of the stream engine. "OK" means available; "FATAL" means unavailable lastErrMsg the latest error message useSystemTime the value of parameter useSystemTime in function createAsofJoinEngine delayedTime the value of parameter delayedTime in function createAsofJoinEngine garbageSize the threshold of the number of records in memory that triggers memory cleaning leftTableNumRows the number of records in the left table of stream engine rightTableNumRows the number of records in the right table of stream engine numMetrics the number of metrics calculated by the stream engine metrics the metacode of the metrics calculated by the stream engine memoryUsed the amount of memory used -
Table EqualJoinEngine returns the following columns about the equal join engine:
Column Name Description name name of the stream engine user name of the user who created the stream engine status status of the stream engine. "OK" means available; "FATAL" means unavailable lastErrMsg the latest error message garbageSize whether the stream engine is triggered as soon as data are ingested into the system leftTableNumRows the number of records that has entered the left table of the stream engine rightTableNumRows the number of records that has entered the right table of the stream engine numMetrics the number of metrics calculated by the stream engine metrics the metacode of the metrics calculated by the stream engine memoryUsed the amount of memory used -
Table StreamDispatchEngine returns the following columns about stream dispatch engines:
Column Name Description name name of the stream engine user name of the user who created the stream engine status status of the stream engine. "OK" means available; "FATAL" means unavailable lastErrMsg the latest error message numRows the number of records that has entered the stream engine memoryUsed the amount of memory used
Examples
share streamTable(10:0,`time`sym`price`qty,[TIMESTAMP,SYMBOL,DOUBLE,INT]) as trades
outputTable1 = table(10000:0, `time`sym`sumQty, [TIMESTAMP, SYMBOL, INT])
outputTable2 = table(1:0, `time`avgPrice`sumqty`Total, [TIMESTAMP,DOUBLE,INT,DOUBLE])
tradesTsAggregator = createTimeSeriesEngine(name="TimeSeriesDemo", windowSize=3, step=3, metrics=<[sum(qty)]>, dummyTable=trades, outputTable=outputTable1, timeColumn=`time, keyColumn=`sym, garbageSize=50)
tradesCsAggregator=createCrossSectionalEngine(name="CrossSectionalDemo", metrics=<[avg(price), sum(qty), sum(price*qty)]>, dummyTable=trades, outputTable=outputTable2, keyColumn=`sym, triggeringPattern=`perRow)
subscribeTable(tableName="trades", actionName="tradesTsAggregator", offset=0, handler=append!{tradesTsAggregator}, msgAsTable=true)
subscribeTable(tableName="trades", actionName="tradesCsAggregator", offset=0, handler=append!{tradesCsAggregator}, msgAsTable=true)
def writeData(n){
timev = 2000.10.08T01:01:01.001 + timestamp(1..n)
symv =take(`A`B, n)
pricev=take(102.1 33.4 73.6 223,n)
qtyv = take(60 74 82 59, n)
insert into trades values(timev, symv, pricev,qtyv)
}
writeData(4);
getStreamEngineStat().TimeSeriesEngine;
getStreamEngineStat().CrossSectionalEngine;