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PONeed to compare very large files around 1.5GB in python
 

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  1. PONeed to compare very large files around 1.5GB in python
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    <pre><code>"DF","00000000@11111.COM","FLTINT1000130394756","26JUL2010","B2C","6799.2" "Rail","00000.POO@GMAIL.COM","NR251764697478","24JUN2011","B2C","2025" "DF","0000650000@YAHOO.COM","NF2513521438550","01JAN2013","B2C","6792" "Bus","00009.GAURAV@GMAIL.COM","NU27012932319739","26JAN2013","B2C","800" "Rail","0000.ANU@GMAIL.COM","NR251764697526","24JUN2011","B2C","595" "Rail","0000MANNU@GMAIL.COM","NR251277005737","29OCT2011","B2C","957" "Rail","0000PRANNOY0000@GMAIL.COM","NR251297862893","21NOV2011","B2C","212" "DF","0000PRANNOY0000@YAHOO.CO.IN","NF251327485543","26JUN2011","B2C","17080" "Rail","0000RAHUL@GMAIL.COM","NR2512012069809","25OCT2012","B2C","5731" "DF","0000SS0@GMAIL.COM","NF251355775967","10MAY2011","B2C","2000" "DF","0001HARISH@GMAIL.COM","NF251352240086","22DEC2010","B2C","4006" "DF","0001HARISH@GMAIL.COM","NF251742087846","12DEC2010","B2C","1000" "DF","0001HARISH@GMAIL.COM","NF252022031180","09DEC2010","B2C","3439" "Rail","000AYUSH@GMAIL.COM","NR2151120122283","25JAN2013","B2C","136" "Rail","000AYUSH@GMAIL.COM","NR2151213260036","28NOV2012","B2C","41" "Rail","000AYUSH@GMAIL.COM","NR2151313264432","29NOV2012","B2C","96" "Rail","000AYUSH@GMAIL.COM","NR2151413266728","29NOV2012","B2C","96" "Rail","000AYUSH@GMAIL.COM","NR2512912359037","08DEC2012","B2C","96" "Rail","000AYUSH@GMAIL.COM","NR2517612385569","12DEC2012","B2C","96" </code></pre> <p>Above is the sample data. Data is sorted according to email addresses and the file is very large around 1.5Gb</p> <p>I want output in another csv file something like this</p> <pre><code>"DF","00000000@11111.COM","FLTINT1000130394756","26JUL2010","B2C","6799.2",1,0 days "Rail","00000.POO@GMAIL.COM","NR251764697478","24JUN2011","B2C","2025",1,0 days "DF","0000650000@YAHOO.COM","NF2513521438550","01JAN2013","B2C","6792",1,0 days "Bus","00009.GAURAV@GMAIL.COM","NU27012932319739","26JAN2013","B2C","800",1,0 days "Rail","0000.ANU@GMAIL.COM","NR251764697526","24JUN2011","B2C","595",1,0 days "Rail","0000MANNU@GMAIL.COM","NR251277005737","29OCT2011","B2C","957",1,0 days "Rail","0000PRANNOY0000@GMAIL.COM","NR251297862893","21NOV2011","B2C","212",1,0 days "DF","0000PRANNOY0000@YAHOO.CO.IN","NF251327485543","26JUN2011","B2C","17080",1,0 days "Rail","0000RAHUL@GMAIL.COM","NR2512012069809","25OCT2012","B2C","5731",1,0 days "DF","0000SS0@GMAIL.COM","NF251355775967","10MAY2011","B2C","2000",1,0 days "DF","0001HARISH@GMAIL.COM","NF251352240086","09DEC2010","B2C","4006",1,0 days "DF","0001HARISH@GMAIL.COM","NF251742087846","12DEC2010","B2C","1000",2,3 days "DF","0001HARISH@GMAIL.COM","NF252022031180","22DEC2010","B2C","3439",3,10 days "Rail","000AYUSH@GMAIL.COM","NR2151213260036","28NOV2012","B2C","41",1,0 days "Rail","000AYUSH@GMAIL.COM","NR2151313264432","29NOV2012","B2C","96",2,1 days "Rail","000AYUSH@GMAIL.COM","NR2151413266728","29NOV2012","B2C","96",3,0 days "Rail","000AYUSH@GMAIL.COM","NR2512912359037","08DEC2012","B2C","96",4,9 days "Rail","000AYUSH@GMAIL.COM","NR2512912359037","08DEC2012","B2C","96",5,0 days "Rail","000AYUSH@GMAIL.COM","NR2517612385569","12DEC2012","B2C","96",6,4 days "Rail","000AYUSH@GMAIL.COM","NR2517612385569","12DEC2012","B2C","96",7,0 days "Rail","000AYUSH@GMAIL.COM","NR2151120122283","25JAN2013","B2C","136",8,44 days "Rail","000AYUSH@GMAIL.COM","NR2151120122283","25JAN2013","B2C","136",9,0 days </code></pre> <p>i.e if entry occurs 1st time i need to append 1 if it occurs 2nd time i need to append 2 and likewise i mean i need to count no of occurences of an email address in the file and if an email exists twice or more i want difference among dates and remember <strong>dates are not sorted</strong> so we have to sort them also against a particular email address and i am looking for a solution in python using numpy or pandas library or any other library that can handle this type of huge data without giving out of bound memory exception i have dual core processor with centos 6.3 and having ram of 4GB</p>
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    1. COPut them in a database. Sort by name, then by date.
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    2. COit sounds like something to do following the Map-Reduce approach
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      1. USManolo
 

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