I have a page that creates bulk users in my application, and I was wondering if it's possible to use the created users and put them in my users.csv file (CSV Data Set Config element) so that I will use those users in the current test only.
The idea is to have dynamic users.csv file each test instead of fixed one, for all concurrent tests.
Yes, You can do in the current test - But in a different thread group when you run consecutively.
Use BeanShell PostProcessor to write the created users in a CSV file as given below in the Thread Group 1.
import org.apache.jmeter.services.FileServer;
f = new FileOutputStream("CSV file Path.csv", true);
p = new PrintStream(f);
p.println(vars.get("username") + "," + vars.get("password"));
p.close();
f.close();
Then you can use CSV Data Set Config to read the same file and get the User Name , Password in the Next Thread Group.
If you want to use it in the same Thread Group, You can write in the CSV file - but use vars.get("username"), vars.get("password") in your test - as you can not read the CSV file yet to be created using CSV Data Set Config.
Related
I have to upload the data from a Snowflake table to Azure BLOB using COPYINTO command. The copy command I have is working for SINGLE = TRUE property but I want to break the in multiple files if the size exceeds 40MB.
For example, There is a table 'TEST' in snowflake with 100MB, I want to upload this data in azure BLOB.
The copy into command should create files in below format
TEST_1.csv (40MB)
TEST_2.csv (40MB)
TEST_3.csv (20MB)
--COPY INTO Command I am using
copy into #stage/test.csv from snowflake.test file_format = (format_name = PRW_CSV_FORMAT) header=true OVERWRITE = TRUE SINGLE = TRUE max_file_size = 40000000
We cannot control the output size of file unloads, only the max file size. The number and size of the files are based on maximum performance as it parallelizes the operation. If you want to control the number/size of files, that would be a feature request. Otherwise, just work out a process outside of Snowflake to combine the files afterward. For more details about unloading, please refer to the blog
I recently asked the question Apache Flume - send only new file contents
I am rephrasing the question in order to learn more and provide more benefitto future users of Flume.
Setup: Two servers, one with a .txt file that gets lines appended to it regularly.
Goal: Use flume TAILDIR source to append the most recently written line to a file on the other server.
Issue: Whenever the source file has a new line of data added, the current configuration appends everything in file on server 1 to the file in server 2. This results in duplicate lines in file 2 and does not properly recreate the file from server 1.
Configuration on server 1:
#configure the agent
agent.sources=r1
agent.channels=k1
agent.sinks=c1
#using memort channel to hold upto 1000 events
agent.channels.k1.type=memory
agent.channels.k1.capacity=1000
agent.channels.k1.transactionCapacity=100
#connect source, channel,sink
agent.sources.r1.channels=k1
agent.sinks.c1.channel=k1
#define source
agent.sources.r1.type=TAILDIR
agent.sources.r1.channels=k1
agent.sources.r1.filegroups=f1
agent.sources.r1.filegroups.f1=/home/tail_test_dir/test.txt
agent.sources.r1.maxBackoffSleep=1000
#connect to another box using avro and send the data
agent.sinks.c1.type=avro
agent.sinks.c1.hostname=10.10.10.4
agent.sinks.c1.port=4545
Configuration on server 2:
#configure the agent
agent.sources=r1
agent.channels=k1
agent.sinks=c1
#using memory channel to hold up to 1000 events
agent.channels.k1.type=memory
agent.channels.k1.capacity=1000
agent.channels.k1.transactionCapacity=100
#connect source, channel, sink
agent.sources.r1.channels=k1
agent.sinks.c1.channel=k1
#here source is listening at the specified port using AVRO for data
agent.sources.r1.type=avro
agent.sources.r1.bind=0.0.0.0
agent.sources.r1.port=4545
#use file_roll and write file at specified directory
agent.sinks.c1.type=file_roll
agent.sinks.c1.sink.directory=/home/Flume_dump
You have to set position json file. Then the source check the position and write only new added lines to sink.
ex) agent.sources.s1.positionFile = /var/log/flume/tail_position.json
There are different lists available in pelicanconf.py such as
SOCIAL = (('Facebook','www.facebook.com'),)
LINKS =
etc.
I want to manage these content and create my own lists by loading these values from an external file which can be edited independently. I tried importing data as a text file using python but it doesn't work. Is there any other way?
What exactly did not work? Can you provide code?
You can execute arbitrary python code in your pelicanconf.py.
Example for a very simple CSV reader:
# in pelicanconf.py
def fn_to_list(fn):
with open(fn, 'r') as res:
return tuple(map(lambda line: tuple(line[:-1].split(';')), res.readlines()))
print(fn_to_list("data"))
CSV file data:
A;1
B;2
C;3
D;4
E;5
F;6
Together, this yields the following when running pelican:
# ...
((u'A', u'1'), (u'B', u'2'), (u'C', u'3'), (u'D', u'4'), (u'E', u'5'), (u'F', u'6'))
# ...
Instead of printing you can also assign this list to a variable, say LINKS.
I have 24 spss files in .sav format in a single folder. All these files have the same structure. I want to run the same syntax on all these files. Is it possible to write a code in spss for this?
You can use the SPSSINC PROCESS FILES user submitted command to do this or write your own macro. So first lets create some very simple fake data to work with.
*FILE HANDLE save /NAME = "Your Handle Here!".
*Creating some fake data.
DATA LIST FREE / X Y.
BEGIN DATA
1 2
3 4
END DATA.
DATASET NAME Test.
SAVE OUTFILE = "save\X1.sav".
SAVE OUTFILE = "save\X2.sav".
SAVE OUTFILE = "save\X3.sav".
EXECUTE.
*Creating a syntax file to call.
DO IF $casenum = 1.
PRINT OUTFILE = "save\TestProcess_SHOWN.sps" /"FREQ X Y.".
END IF.
EXECUTE.
Now we can use the SPSSINC PROCESS FILES command to specify the sav files in the folder and apply the TestProcess_SHOWN.sps syntax to each of those files.
*Now example calling the syntax.
SPSSINC PROCESS FILES INPUTDATA="save\X*.sav"
SYNTAX="save\TestProcess_SHOWN.sps"
OUTPUTDATADIR="save" CONTINUEONERROR=YES
VIEWERFILE= "save\Results.spv" CLOSEDATA=NO
MACRONAME="!JOB"
/MACRODEFS ITEMS.
Another (less advanced) way is to use the command INSERT. To do so, repeatedly GET each sav-file, run the syntax with INSERT, and sav the file. Probably something like this:
get 'file1.sav'.
insert file='syntax.sps'.
save outf='file1_v2.sav'.
dataset close all.
get 'file2.sav'.
insert file='syntax.sps'.
save outf='file2_v2.sav'.
etc etc.
Good luck!
If the Syntax you need to run is completely independent of the files then you can either use: INSERT FILE = 'Syntax.sps' or put the code in a macro e.g.
Define !Syntax ()
* Put Syntax here
!EndDefine.
You can then run either of these 'manually';
get file = 'file1.sav'.
insert file='syntax.sps'.
save outfile ='file1_v2.sav'.
Or
get file = 'file1.sav'.
!Syntax.
save outfile ='file1_v2.sav'.
Or if the files follow a reasonably strict naming structure you can embed either of the above in a simple bit of python;
Begin Program.
imports spss
for i in range(0, 24 + 1):
syntax = "get file = 'file" + str(i) + ".sav.\n"
syntax += "insert file='syntax.sps'.\n"
syntax += "save outfile ='file1_v2.sav'.\n"
print syntax
spss.Submit(syntax)
End Program.
Apache Pig v0.7 can read gzipped files with no extra effort on my part, e.g.:
MyData = LOAD '/tmp/data.csv.gz' USING PigStorage(',') AS (timestamp, user, url);
I can process that data and output it to disk okay:
PerUser = GROUP MyData BY user;
UserCount = FOREACH PerUser GENERATE group AS user, COUNT(MyData) AS count;
STORE UserCount INTO '/tmp/usercount' USING PigStorage(',');
But the output file isn't compressed:
/tmp/usercount/part-r-00000
Is there a way of telling the STORE command to output content in gzip format? Note that ideally I'd like an answer applicable for Pig 0.6 as I wish to use Amazon Elastic MapReduce; but if there's a solution for any version of Pig I'd like to hear it.
There are two ways:
As mentioned above in the storage you can say the output directory as
usercount.gz
STORE UserCount INTO '/tmp/usercount.gz' USING PigStorage(',');
Set compression method in your script.
set output.compression.enabled true;
set output.compression.codec org.apache.hadoop.io.compress.GzipCodec;
For Pig r0.8.0 the answer is as simple as giving your output path an extension of ".gz" (or ".bz" should you prefer bzip).
The last line of your code should be amended to read:
STORE UserCount INTO '/tmp/usercount.gz' USING PigStorage(',');
Per your example, your output file would then be found as
/tmp/usercount.gz/part-r-00000.gz
For more information, see: https://pig.apache.org/docs/r0.8.1/piglatin_ref2.html#PigStorage
According to the Pig documentation for PigStorage, there are 2 ways to do this
Specifying the compression format using the 'STORE' statement
STORE UserCount INTO '/tmp/usercount.gz' USING PigStorage(',');
STORE UserCount INTO '/tmp/usercount.bz2' USING PigStorage(',');
STORE UserCount INTO '/tmp/usercount.lzo' USING PigStorage(',');
Notice the above statements. Pig supports 3 compression formats, i.e GZip, BZip2 and LZO. For getting LZO to work you have to install it separately. See here for more information about lzo.
Specifying compression via job properties
By setting the following properties in your pig script, i.e output.compression.enabled and output.compression.codec via the following code
set output.compression.enabled true;
and
set output.compression.codec com.hadoop.compression.lzo.LzopCodec;
set output.compression.codec org.apache.hadoop.io.compress.GzipCodec;
set output.compression.codec org.apache.hadoop.io.compress.BZip2Codec;