Aq Log Data
Essentia’s Environment
In this tutorial we just want to setup a simple Essentia environment, one that runs on our local computer and scans our local filesystem for the aq log data data located in the casestudies/aq/aqlogs directory. If you are not already in the casestudies/aq/ directory, please switch into it now. We save the following commands to aqlog.sh:
1 ess cluster set local
2 ess purge local
3
4 #ess udbd stop
5 ess server reset
6
7 ess create database aqlogday --ports=1
8 ess create vector aqlogday s,pkey:day i,+add:pagecount i,+add:hitcount
9 # Create a vector to aggregate (count) the number of pages and hits seen or used by day.
10
11 ess create database aqloghour --ports=1
12 ess create vector aqloghour s,pkey:hour i,+add:pagecount i,+add:hitcount
13 # Create a vector to aggregate (count) the number of pages and hits seen or used by hour.
14
15 ess create database aqlogmonth --ports=1
16 ess create vector aqlogmonth s,pkey:month i,+add:pagecount i,+add:hitcount
17 # Create a vector to aggregate (count) the number of pages and hits seen or used over each month of data.
18
19 ess create database aqlogdayoftheweek --ports=1
20 ess create vector aqlogdayoftheweek s,pkey:dayoftheweek i,+add:pagecount i,+add:hitcount
21 # Create a vector to aggregate (count) the number of pages and hits seen or used by day of the week.
22
23 #ess udbd start
24 ess udbd restart
25
26 ess select local
27
28 ess category add aqlogs "$HOME/EssentiaPublic/*casestudies/aq/aqlogs/*.gz" --dateregex ".*-d-[:%Y:][:%m:][:%d:]-.*"
29
30 ess summary
31
32 # Check Essentia Version Number for Compatibility
33 EssVersion=`ess -v 2>&1 | aq_pp -f,eok,sep=':' - -d X s,trm:EssentiaVersion -filt '\$RowNum==1' \
34 -filt 'EssentiaVersion!="3.0.9.12"' -o,notitle - 2>/dev/null`
35 if [ -z "$EssVersion" ]
36 then
37 oldmod="-emod rt "
38 else
39 oldmod=""
40 fi
41
42 ess stream aqlogs "2014-06-13" "2014-08-15" "aq_pp $oldmod -f,+1,eok - -d %cols -filt 'status == 200 || status == 304' -eval i:hitcount '1' \
43 -if -filt '(PatCmp(page, \"*.html[?,#]?*\", \"ncas\") || PatCmp(page, \"*.htm[?,#]?*\", \"ncas\") || PatCmp(page, \"*.php[?,#]?*\", \"ncas\") || PatCmp(page, \"*.asp[?,#]?*\", \"ncas\") || PatCmp(page, \"*/\", \"ncas\") || PatCmp(page, \"*.php\", \"ncas\"))' -eval i:pagecount '1' -eval s:pageurl 'page' \
44 -else -eval pagecount '0' -endif -eval s:month 'TimeToDate(t,\"%B\")' -eval s:day 'TimeToDate(t,\"%d\")' -eval s:dayoftheweek 'TimeToDate(t,\"%a\")' -eval s:hour 'TimeToDate(t,\"%H\")' \
45 -ddef -udb -imp aqlogday:aqlogday -imp aqloghour:aqloghour -imp aqlogmonth:aqlogmonth -imp aqlogdayoftheweek:aqlogdayoftheweek" --debug
46
47 # Stream your aq logs from the startdate and enddate you specify into the following command.
48 # Then pipe the data into our preprocessor (aq_pp) and tell Essentia to use the column specification it determined. Filter on status so that you only include the 'good' http status codes that correspond to actual views.
49 # Create a column that you can aggregate for each record to keep track of hits and another column to group the data by. Filter on page to eliminate any viewed files that dont have certain elements in their filename.
50 # If this filter returns true, count that file as a page and save the file to a column called pageurl. If the filter returns false then the file is not counted as a page.
51 # Convert the t column to a date and extract the month ("December"...), day ("01"...), dayoftheweek ("Sun"...), and hour ("00" to "23") into their respective columns.
52 # Import the modified and reduced data into the four vectors in the databases you defined above so that the attributes defined there can be applied.
and then run
sh aqlog.sh
This executes the essentia commands in aqlog.sh to load the aq logs into the UDB database.
read.essentia
With the environment setup, we can now use read.essentia to execute an essentia script that exports the data from the Essentia database in csv format and then read it into R.
The read.essentia function takes one argument: file, which can contain any arguments that you could typically pass to a bash script.
The output can be saved into an R dataframe
**my_dataframe_name** <- read.essentia(file)
read.essentia requires you to store each essentia query in a bash script. Thus we save the following statement to aqlogday.sh:
# This statement exports the day vector from its database. ess exec "aq_udb -exp aqlogday:aqlogday"
to export the data from vector aqlogday in the aqlogday database. Similarly we save:
# This statement exports the hour vector from its database. ess exec "aq_udb -exp aqloghour:aqloghour"
into aqloghour.sh,
# This statement exports the day-of-the-week vector from its database. ess exec "aq_udb -exp aqlogdayoftheweek:aqlogdayoftheweek"
into aqlogdayoftheweek.sh, and
# This statement exports the month vector from its database. ess exec "aq_udb -exp aqlogmonth:aqlogmonth"
into aqlogmonth.sh.
Then we simply have R run:
system("time bash aqlog.sh")
# Run the essentia statements written in aqlog.sh.
# These statements load the aqlog data into four databases to get the total number of pages and # hits by day, hour, month, and day-of-the-week.
library(RESS)
# Load Essentia's R Integration package.
aqlogday <- read.essentia('aqlogday.sh')
# Call read.essentia to execute the essentia statement written in aqlogday.sh and save it's output into to an R dataframe.
aqloghour <- read.essentia('aqloghour.sh')
# Call read.essentia to execute the essentia statement written in aqloghour.sh and save it's output into to an R dataframe.
aqlogmonth <- read.essentia('aqlogmonth.sh')
# Call read.essentia to execute the essentia statement written in aqlogmonth.sh and save it's output into to an R dataframe.
aqlogdayoftheweek <- read.essentia('aqlogdayoftheweek.sh')
# Call read.essentia to execute the essentia statement written in aqlogdayoftheweek.sh and save it's output into to an R dataframe.
We are now free to analyze this data using the massive variety of R functions and methods. To get a few quick plots of this data, we can run the R commands written in analyzeaqlog.R:
source("analyzeaqlog.R", echo=FALSE)
# Run the R commands written in analyzeaqlog.R to analyze the data in the dataframes we just created.
# Turn echo to TRUE to make the output less results-oriented and easier to debug.
This creates plots of the number of pages and hits versus month, day, day of the week, and hour.
Next Steps
This tutorial was meant to continue to familiarize the user with Essentia’s R Integration and demonstrated how to use read.essentia to send data through Essentia’s preprocessor and into R. To see more analysis of complex datasets, please read through our R Apache Analysis use case.