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December 18, 2015 06:08
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flow count with exponential moving average
data comes from Postgres DB
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# install.packages("RPostgreSQL") | |
# install.packages("zoo") | |
# Notes: EMA - Exponential moving average with alpha=0.05 | |
library(RPostgreSQL) | |
library(TTR) | |
drv <- dbDriver("PostgreSQL") | |
##con <- dbConnect(drv, dbname="probedb", user="postgres", host="192.168.132.111") | |
con <- dbConnect(drv, dbname="1", user="postgres", host="192.168.132.111") | |
# dbListConnections(drv) | |
# dbGetInfo(drv) | |
# summary(con) | |
rs <- dbSendQuery( | |
con, | |
"SELECT start_time_sec AS \"timestamp\", | |
count(DISTINCT flow_id)::numeric / | |
count(DISTINCT CASE d WHEN 1 THEN ip_addr_1 ELSE ip_addr_2 END) AS flow_count | |
FROM long_flow_samples, (VALUES (1),(2)) AS d(d) | |
WHERE ( d!=1 OR byte_count_1!=0 ) AND ( d!=1 OR byte_count_1!=0 ) | |
GROUP BY start_time_sec"); | |
#rs <- dbSendQuery( | |
# con, | |
# "SELECT * FROM prx_flow_counts_per_sec( NULL, NULL, '{98e95c92-235c-699d-08dd-d278a59a1675}')") | |
cnts <- fetch(rs,n=-1) | |
plot( | |
cnts$flow_count ~ cnts$timestamp,, | |
col="red", | |
xlab="timestamp (sec)", | |
ylab="Flow Counts", | |
main="Incoming flow counts per sec") | |
lines(cnts$timestamp, EMA(cnts$flow_count,n=1,ratio=0.05), col="blue",lwd=2) |
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