Save joined dataset
Saving to new Cassandra Table and output JSON file
Github repository Path: examples/dataset-join-03 Language: Python v3.5
- Previous Requirements
- Data sources
Description
This is a standalone python example which runs directly onto python interpreter. The core is pyspark which is a python package that is the wrapper of Apache Spark.
It is very similar to previous dataset-join-02. However, this is independent from spark-shell or spark-submit. Both save back results to a Cassandra’s table. Furthermore, dataset-join-03 writes to disk on a JSON format output file.
Explanation
Libraries used by this example:
import os, sys
import pandas as pd
os.putenv('PYTHONIOENCODING','UTF-8')
from pyspark import SparkContext, SparkConf
from pyspark.sql import SQLContext, SparkSession
Setting up Cassandra-ready spark session
spark = (
SparkSession.builder
.appName('SparkCassandraApp')
.config('spark.cassandra.connection.host', 'localhost')
.config('spark.cassandra.connection.port', '9042')
.config('spark.cassandra.output.consistency.level','ONE')
.master('local[2]')
.getOrCreate()
)
Loading data of people
ds_people = (
sqlContext
.read
.format('org.apache.spark.sql.cassandra')
.options(table='mock_data', keyspace='examples')
.load()
.filter('drinker == "Daily"')
)
The same with cars
ds_cars = (
sqlContext
.read
.format('org.apache.spark.sql.cassandra')
.options(table='mock_cars', keyspace='examples')
.load()
)
Join cars with owners
ds_drinkers = (
ds_people
.join(ds_cars,ds_people['id'] == ds_cars['id_owner'])
.select('id','email','car_id','car_make','car_model')
)
Table is created if no exists, otherwise exception is raise but silenced
Nowadays it doesn’t work, but in Scala dataset-join-02 it works flawlessly. I reported to maintener at datastax
try:
# this method doesn't work with pyspark (in scala works fine)
ds_drinkers.createCassandraTable('examples', 'cars_owned_by_drinkers', partitionKeyColumns = ['id','car_id'])
except:
None
Saving joined dataset back to Cassandra
(
ds_drinkers
.write
.mode('append')
.format('org.apache.spark.sql.cassandra')
.options(table = 'cars_owned_by_drinkers', keyspace = 'examples')
.save()
)
To test the result, it loads again new data into Spark’s DataFrame
ds_cars = (
sqlContext
.read
.format('org.apache.spark.sql.cassandra')
.options(table='cars_owned_by_drinkers', keyspace='examples')
.load()
)
Loading data into pandas in order to save to file system, although It could be post in an HTTP connection or something else
df = ds_cars.toPandas()
df.to_json('./output.json')
Results output.json
{
"id":{
"0":532,
"1":782,
"2":266,
"3":900,
"4":807,
"5":590,
"6":754,
"7":387,
"8":904,
"9":492,
"10":699,
"11":564,
"12":779,
"13":26,
"14":796,
"15":149,
"16":671,
"17":903,
"18":635,
"19":211,
"20":233,
"21":346,
"22":136,
"23":405,
"24":681,
"25":940,
"26":358,
"27":695,
"28":572,
"29":886,
"30":561,
"31":185,
"32":203,
"33":700,
"34":686,
"35":811,
"36":331,
"37":4,
"38":400,
"39":175,
"40":255,
"41":515,
"42":687,
"43":76,
"44":876,
"45":605,
"46":249,
"47":86,
"48":792,
"49":302,
"50":528,
"51":439,
"52":914,
"53":712,
"54":868,
"55":594,
"56":218,
"57":84,
"58":53,
"59":872,
"60":533,
"61":705,
"62":800,
"63":159,
"64":677,
"65":499,
"66":969,
"67":690,
"68":408,
"69":225,
"70":931,
"71":489,
"72":336,
"73":99,
"74":867,
"75":449,
"76":882,
"77":986,
"78":395,
"79":755,
"80":960,
"81":366,
"82":664,
"83":787,
"84":106,
"85":454,
"86":915,
"87":230,
"88":62,
"89":271,
"90":992,
"91":920,
"92":342,
"93":327,
"94":953,
"95":697,
"96":500,
"97":726,
"98":350,
"99":784,
"100":473,
"101":596,
"102":575,
"103":849,
"104":679,
"105":802,
"106":501,
"107":247,
"108":107,
"109":854,
"110":24,
"111":861,
"112":642,
"113":936,
"114":420,
"115":621,
"116":367,
"117":864,
"118":884,
"119":145,
"120":885,
"121":682,
"122":146,
"123":987,
"124":780,
"125":286,
"126":231,
"127":812,
"128":989,
"129":828,
"130":643,
"131":758,
"132":171,
"133":569,
"134":332,
"135":724,
"136":616,
"137":955,
"138":276,
"139":534,
"140":111,
"141":67,
"142":776,
"143":478,
"144":573
},
"car_id":{
"0":"c5577b3d-58fd-45d6-b3cc-15c4ed37f7d9",
"1":"9578d049-958d-44e8-b611-4533c0a71074",
"2":"7378adb7-a965-4795-ae7d-aebf469511e4",
"3":"81f330da-c322-43c3-8536-bd92bc22555c",
"4":"93497ddc-bea9-4af1-927c-8a2ab24a5699",
"5":"c625e58b-8b03-4df4-ac3f-f55a824f3f59",
"6":"b8d648cb-e4b8-4c14-853c-0900531bb142",
"7":"6bf737b4-3084-4af7-ace7-315136f93eda",
"8":"78b44210-090a-4256-ba3a-35235bb36b0e",
"9":"b6d7f202-6989-4726-bc33-2fb278380602",
"10":"5dbbdb37-88f3-4a70-8026-32849f2c2c05",
"11":"ff80ce4d-5847-4d38-b905-b211ea011e02",
"12":"46395c7c-77a2-401f-80eb-96bf3185ab97",
"13":"5154213c-5875-40d6-9546-17255c8e278e",
"14":"7b6919ce-b879-4e3d-9a44-91a8ae0f6644",
"15":"25c0bd13-c560-4421-b958-1122bd3771a0",
"16":"43187cd5-2316-4b81-b427-e9e7d752600a",
"17":"1fe04043-4c8c-43ca-8e69-502783a6f196",
"18":"263775e9-c07e-46a4-a693-3d62b527abbd",
"19":"4836950f-68c4-4673-a79a-d45e67b40f5f",
"20":"dfef6677-8ba7-49b5-bcdd-fa1d45888fcf",
"21":"d50c8068-fe28-4a2b-88bb-8b1269bee640",
"22":"395c1530-32f2-4084-ae12-217cd44e7893",
"23":"b4b86ee1-5181-4a2f-8a83-14834b205d37",
"24":"93f3735d-60be-4974-b01d-ce764b972a18",
"25":"d754be9b-9e4f-4c90-a88e-e9d93b7b4a31",
"26":"f9f13728-a47e-40b4-b3d8-52655fdce923",
"27":"ee1d5037-4f0c-4278-8f74-64a2c4280be1",
"28":"2e386c1c-075e-48f5-8dee-e9721d4c3412",
"29":"a3f944df-3429-42d3-b566-63c0923697ea",
"30":"75d00261-673f-4bbb-b0b2-44604f04fc73",
"31":"46a14981-3479-4882-81ff-a176c90790e6",
"32":"f8b86ad4-6e45-43ef-ab5b-fca11c3da48a",
"33":"d23880d0-39d2-4302-834d-758a5f7d385b",
"34":"9403d296-574d-41c9-8dd9-6943555bb873",
"35":"50281ba9-8cd4-45fe-aa58-96cdfaa9ec75",
"36":"cc5df18b-a342-4130-9db0-bf1ae7987164",
"37":"b507aeff-f208-4e45-9da3-5c67ee8bd4a8",
"38":"b2228c61-112b-4d57-ad82-d53f9490fb3b",
"39":"ddb65ebd-c781-433d-a08d-9aa5c394a9be",
"40":"1b5d41f8-7b81-412a-9398-78f9125e859c",
"41":"b7187e24-7f29-4e6f-a632-989dbee52164",
"42":"feb4a229-4aa7-4b7f-9421-b6633140b6ac",
"43":"e6e6a3d4-3283-4adc-ad19-bb00c2d48495",
"44":"a65f9c4e-a170-4f89-a80c-251ca79c9843",
"45":"6f05d852-b43c-4c8f-bc21-17b832a1572f",
"46":"144c36fc-6bbf-45c0-b0fd-5d2b6460cb01",
"47":"c73802db-c188-4c7b-a8bf-e1bc7c63cf47",
"48":"7231d3f7-0613-4f1d-8d2b-35112d221540",
"49":"98ddfe24-25e9-49b9-b791-42a886ef8752",
"50":"4478563f-b184-4ebb-8615-d84b7c249f56",
"51":"7c507426-3532-40ce-9ab3-729904068ed3",
"52":"7f69d4de-1ffb-4ac3-b556-b01a84bfefe9",
"53":"d73b662d-14be-49d7-859f-9d20e1e376c7",
"54":"17029efb-141d-4ced-bb82-56a8c50badea",
"55":"385511c1-43f2-4b0f-bba0-b923ed164ad1",
"56":"20815e0c-0877-4cdf-b61f-48f95f9510ea",
"57":"9ad097c9-2970-4480-b15b-c2098f8e6141",
"58":"a56327ed-4a43-4910-a18e-d4545d285bbe",
"59":"96735569-2d20-4575-a36e-602ff8952a10",
"60":"accde034-98ca-4926-ad58-25723c7b1897",
"61":"f47529fe-ca9a-49df-9d98-4705dcbe971b",
"62":"da7424ef-a2bb-4cac-8795-e231e83d1ddb",
"63":"8818c957-eff4-410d-9d9b-8b26b47253f9",
"64":"e59e2f3b-0252-4401-880f-42e6997beda8",
"65":"be076613-634c-4164-9168-5c2d65793940",
"66":"3a56978e-7724-40b1-8f72-6796cd1961b3",
"67":"f2bb0131-b1a9-4746-81be-db8bd16696a6",
"68":"6f5e9145-be17-4e3c-9d4c-506d89e0fe50",
"69":"646f88ba-091a-42e8-8fca-ee9a49a9c28e",
"70":"062044a1-38cf-47ec-a9ef-5867de7c9940",
"71":"221860c4-479a-44aa-bb43-a1a70ca05dd1",
"72":"3f3a6820-da3d-4912-b269-37ba06090009",
"73":"819fb204-ca5c-4488-af6a-c50b4e24b2d6",
"74":"138d12ea-ee89-453f-a646-b9cf2176ee40",
"75":"943eea59-9ea7-4117-b898-0de5b3bad50b",
"76":"834f8603-b758-4c0a-8915-362c473635fa",
"77":"e4ec2a2b-c5da-4071-a7c8-18d76e851588",
"78":"2c318882-4fa4-4799-8e1e-191e3fcb80c8",
"79":"6d6085da-46ea-4726-9c90-f0a6a66fc2b4",
"80":"fbd58958-17ae-4ce7-8137-b4edb17abbdd",
"81":"eab42c64-fd79-488a-addc-e107a624b58d",
"82":"f43b0025-3b28-4cb4-855e-b52296936c78",
"83":"83f00240-f54d-4c44-b5d9-062f9d1d607e",
"84":"e97c2135-b69a-4195-96e9-eddc23478bbd",
"85":"7dde4b48-ae0a-4278-85e5-56b1349d224c",
"86":"c715acaa-fa00-40bd-9b2e-27547431e8b6",
"87":"bc3e072d-608d-42ab-a19c-5176f9db1045",
"88":"2f0bb122-f3cc-4f77-b0cc-7cc668369533",
"89":"12955ad9-5905-479a-a5d9-2c74a12a62cf",
"90":"ab8b79bf-0ae4-4bdd-ba7b-800340bf20b7",
"91":"f2aa4a29-d8d3-48df-9e5c-d0c25ee1f64b",
"92":"6511b562-99f3-46dc-8902-6ca9eb006152",
"93":"a461cf67-5cc5-493b-a3f9-d2f9c7aba085",
"94":"caae32bc-449f-4b49-9d1c-61ac2f295fdd",
"95":"da7954e2-c84c-4f93-b7b8-d713a7f591a1",
"96":"c09eb254-385f-4a16-bc8d-bfcd73570a8e",
"97":"3a6d26a0-fcb0-43c9-9ad2-768e0d2daa36",
"98":"e8e9eda3-08e9-4258-bd81-7a49dd5733c7",
"99":"ef6d658f-c203-4d1a-9a4f-738a8bb75a50",
"100":"b02b9f6e-4e01-4659-864c-9389f36af2fa",
"101":"4946ca8b-2fda-41dd-b877-316e9453a6cf",
"102":"2c9e6551-ecb5-481a-b3e8-0d63c76262a3",
"103":"c996a26e-010d-4802-b33b-d93ded897e8c",
"104":"ecf20a68-56d0-4531-b93e-e12b3fec0e17",
"105":"abe7b6f8-ef1f-4178-a362-54337fa3c223",
"106":"62ef80b9-b117-45b7-9282-24bfa8ae353e",
"107":"3663bdfc-941a-449e-8a2e-ae7343ae3448",
"108":"0edb48ee-6856-481f-b48f-0b4e15ac253b",
"109":"17920319-cf3b-4149-81e5-c008fd47c1cc",
"110":"c0ebeed5-3aa4-47c3-a229-fbc8bbe28541",
"111":"5b6dd8d9-461c-476d-8512-53e663219495",
"112":"43655c28-5876-4295-88eb-858242319b74",
"113":"c19409de-11fe-48c0-8457-ef2b8a98e463",
"114":"5a0c62f7-41a6-4f62-9006-28c78d53e087",
"115":"84f11176-b9e7-4e84-94be-c81523db4612",
"116":"e4c27519-5ec3-49d7-8bd6-2cc468a23c20",
"117":"b7bdbd74-eb9f-46d0-9d11-a5840c841b6b",
"118":"0262971d-92a1-4bbd-bd15-b1804957bcd1",
"119":"ea355147-0401-4572-b881-b139b8ff6327",
"120":"31d3023e-4460-4328-82d0-c6820430eeeb",
"121":"48f0b996-ad91-4915-893c-f3138ff5912d",
"122":"af362e0b-bb1b-403c-97ef-71f11e4a7f79",
"123":"b01ccf55-a39c-49c9-ac62-692a80b72ee6",
"124":"5d0b3cf7-5405-4238-b61e-5e6c63e04a46",
"125":"570234a5-abaf-4ca9-b14a-143e44421d18",
"126":"6025fff5-b649-460c-b55f-3d0d4e449655",
"127":"ecb86424-d673-41ad-a9e9-2be25462587b",
"128":"9431564f-28a6-4953-bb43-9fb69a84636c",
"129":"309de1f7-a4a6-470f-a8d5-0e5370f5d350",
"130":"4a5a4c68-bd9d-440e-965c-9440444f5f76",
"131":"7a9fcdc7-e01b-4763-8e34-366c4c0e286e",
"132":"891588a4-741e-4296-84ab-c64b842024a2",
"133":"f42caffd-6934-4c37-825e-cf931b7bb497",
"134":"1ed079a9-7058-4a8c-93b6-bf2ae2d34e7d",
"135":"a41e2d2b-404e-4fb9-aff6-1aa65cd85491",
"136":"877bb149-a37a-4964-99f8-9512949d3afb",
"137":"b91c2b8d-7e77-41c8-9d22-3c2ab0f74b55",
"138":"aa6fff29-47d9-4f7a-b4ef-4359e821eb27",
"139":"cabfe53f-b17c-4b42-b101-6807322ade8e",
"140":"59d2f3a2-a7cf-4da1-bfe0-40b89323caa9",
"141":"0660a94e-59fa-48b3-8ac6-1c7542bcad35",
"142":"ea2eee7c-15ad-4284-ba94-fd50cf8ff3fd",
"143":"2af47107-975d-420d-a300-e6dfcca4ff81",
"144":"30fc4c2b-55cb-456c-a56a-862cfe2a0063"
},
"car_make":{
"0":"Mazda",
"1":"Volvo",
"2":"Oldsmobile",
"3":"Mazda",
"4":"Ford",
"5":"Pontiac",
"6":"Pontiac",
"7":"Mercedes-Benz",
"8":"Buick",
"9":"Pontiac",
"10":"Suzuki",
"11":"Oldsmobile",
"12":"Nissan",
"13":"Mercedes-Benz",
"14":"Pontiac",
"15":"Chevrolet",
"16":"Hyundai",
"17":"Buick",
"18":"Buick",
"19":"Plymouth",
"20":"Ford",
"21":"Chevrolet",
"22":"Ford",
"23":"Toyota",
"24":"Ford",
"25":"Land Rover",
"26":"Lotus",
"27":"Mercedes-Benz",
"28":"Cadillac",
"29":"Mitsubishi",
"30":"Nissan",
"31":"Pontiac",
"32":"Mercury",
"33":"Porsche",
"34":"Mercury",
"35":"Mercury",
"36":"Porsche",
"37":"Ford",
"38":"GMC",
"39":"Eagle",
"40":"Chevrolet",
"41":"Toyota",
"42":"Chevrolet",
"43":"Subaru",
"44":"Chevrolet",
"45":"Volvo",
"46":"Buick",
"47":"Lotus",
"48":"Bentley",
"49":"Mitsubishi",
"50":"Audi",
"51":"Honda",
"52":"Subaru",
"53":"Dodge",
"54":"Ford",
"55":"Mitsubishi",
"56":"Mazda",
"57":"Ford",
"58":"Mazda",
"59":"MINI",
"60":"Volkswagen",
"61":"Acura",
"62":"Ford",
"63":"Honda",
"64":"Buick",
"65":"Audi",
"66":"Pontiac",
"67":"Plymouth",
"68":"Nissan",
"69":"Volvo",
"70":"BMW",
"71":"Lotus",
"72":"Subaru",
"73":"Alfa Romeo",
"74":"Mitsubishi",
"75":"Volkswagen",
"76":"Ford",
"77":"Jaguar",
"78":"Chevrolet",
"79":"Ferrari",
"80":"Mercedes-Benz",
"81":"Cadillac",
"82":"BMW",
"83":"Suzuki",
"84":"Ford",
"85":"Toyota",
"86":"Acura",
"87":"Pontiac",
"88":"Pontiac",
"89":"Pontiac",
"90":"Volvo",
"91":"Suzuki",
"92":"Toyota",
"93":"Mazda",
"94":"Buick",
"95":"Chrysler",
"96":"Saab",
"97":"Acura",
"98":"Aston Martin",
"99":"Volvo",
"100":"Mercury",
"101":"Dodge",
"102":"Bentley",
"103":"Chevrolet",
"104":"Honda",
"105":"Mitsubishi",
"106":"Chrysler",
"107":"Buick",
"108":"Honda",
"109":"Volkswagen",
"110":"Lincoln",
"111":"BMW",
"112":"Maserati",
"113":"Eagle",
"114":"Volkswagen",
"115":"Mercury",
"116":"Plymouth",
"117":"Saab",
"118":"Audi",
"119":"Hyundai",
"120":"Nissan",
"121":"Mercedes-Benz",
"122":"Cadillac",
"123":"Mitsubishi",
"124":"Subaru",
"125":"Volvo",
"126":"Saturn",
"127":"Subaru",
"128":"Lexus",
"129":"Mercury",
"130":"Buick",
"131":"Suzuki",
"132":"Volkswagen",
"133":"Dodge",
"134":"Audi",
"135":"Maybach",
"136":"Jaguar",
"137":"Chevrolet",
"138":"Dodge",
"139":"Chevrolet",
"140":"GMC",
"141":"Subaru",
"142":"GMC",
"143":"Mercedes-Benz",
"144":"BMW"
},
"car_model":{
"0":"RX-7",
"1":"XC70",
"2":"Achieva",
"3":"Mazda6",
"4":"Excursion",
"5":"Fiero",
"6":"LeMans",
"7":"E-Class",
"8":"Rainier",
"9":"GTO",
"10":"Aerio",
"11":"Alero",
"12":"Sentra",
"13":"CL-Class",
"14":"Grand Prix",
"15":"S10",
"16":"Sonata",
"17":"LeSabre",
"18":"Enclave",
"19":"Neon",
"20":"E350",
"21":"Camaro",
"22":"Crown Victoria",
"23":"Camry",
"24":"Fusion",
"25":"Range Rover",
"26":"Evora",
"27":"CL-Class",
"28":"XLR-V",
"29":"L300",
"30":"Xterra",
"31":"Trans Sport",
"32":"Cougar",
"33":"928",
"34":"Grand Marquis",
"35":"Mountaineer",
"36":"Boxster",
"37":"Aerostar",
"38":"Yukon",
"39":"Talon",
"40":"S10",
"41":"4Runner",
"42":"Venture",
"43":"Forester",
"44":"Express 1500",
"45":"S60",
"46":"Park Avenue",
"47":"Esprit",
"48":"Continental Flying Spur",
"49":"Chariot",
"50":"riolet",
"51":"Fit",
"52":"Legacy",
"53":"Dynasty",
"54":"E250",
"55":"Pajero",
"56":"Tribute",
"57":"Explorer Sport Trac",
"58":"RX-7",
"59":"Cooper",
"60":"R32",
"61":"NSX",
"62":"F350",
"63":"Passport",
"64":"Park Avenue",
"65":"riolet",
"66":"Firebird",
"67":"Voyager",
"68":"300ZX",
"69":"S60",
"70":"X5",
"71":"Elise",
"72":"Legacy",
"73":"Spider",
"74":"Montero",
"75":"Scirocco",
"76":"Ranger",
"77":"XK Series",
"78":"Uplander",
"79":"612 Scaglietti",
"80":"190E",
"81":"XLR-V",
"82":"Z4",
"83":"SX4",
"84":"EXP",
"85":"Corolla",
"86":"RL",
"87":"Bonneville",
"88":"Torrent",
"89":"Bonneville",
"90":"S80",
"91":"Swift",
"92":"T100",
"93":"RX-7",
"94":"Rendezvous",
"95":"Cirrus",
"96":"900",
"97":"Integra",
"98":"V8 Vantage",
"99":"XC60",
"100":"Tracer",
"101":"Durango",
"102":"Continental GTC",
"103":"Colorado",
"104":"Accord",
"105":"Eclipse",
"106":"Voyager",
"107":"Somerset",
"108":"CR-X",
"109":"Touareg 2",
"110":"Continental",
"111":"Z3",
"112":"Quattroporte",
"113":"Talon",
"114":"Jetta",
"115":"Mariner",
"116":"Grand Voyager",
"117":"9000",
"118":"V8",
"119":"Elantra",
"120":"200SX",
"121":"S-Class",
"122":"XLR-V",
"123":"Pajero",
"124":"Tribeca",
"125":"XC70",
"126":"Ion",
"127":"Legacy",
"128":"ES",
"129":"Cougar",
"130":"Regal",
"131":"Grand Vitara",
"132":"Cabriolet",
"133":"Dakota",
"134":"S6",
"135":"57S",
"136":"XK",
"137":"Impala",
"138":"Grand Caravan",
"139":"Express 1500",
"140":"Sierra 1500",
"141":"Legacy",
"142":"Sonoma",
"143":"SL-Class",
"144":"X5"
},
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"5":"tdickinge@guardian.co.uk",
"6":"jsaffrinky@ebay.co.uk",
"7":"cdimmackar@macromedia.com",
"8":"mpattlelp4@plala.or.jp",
"9":"trainforddo@rakuten.co.jp",
"10":"ejendrickejf@twitter.com",
"11":"mbrafieldfo@google.com.br",
"12":"nfuggleln@usa.gov",
"13":"bcoxonq@unc.edu",
"14":"cstrathmanm4@joomla.org",
"15":"mscogings45@ehow.com",
"16":"criggollin@fastcompany.com",
"17":"lludwikiewiczp3@nps.gov",
"18":"aglandonhn@cmu.edu",
"19":"dbickerstaffe5v@wp.com",
"20":"msindle6h@photobucket.com",
"21":"aandryushin9m@salon.com",
"22":"nabad3s@homestead.com",
"23":"hmoralasb9@ed.gov",
"24":"cjuneix@gmpg.org",
"25":"kbeckettq4@printfriendly.com",
"26":"aastbury9y@mac.com",
"27":"gredfordjb@samsung.com",
"28":"pshimonyfw@harvard.edu",
"29":"lwoolacottom@cornell.edu",
"30":"bbromwichfl@nba.com",
"31":"emunkley55@w3.org",
"32":"dmaxwale5n@zdnet.com",
"33":"jneashamjg@gov.uk",
"34":"hhardyj2@ocn.ne.jp",
"35":"lsottellmj@about.com",
"36":"crollings97@meetup.com",
"37":"agaydon4@ted.com",
"38":"cmalbonb4@hugedomains.com",
"39":"mmccuffie4v@geocities.jp",
"40":"mfulbrook73@seesaa.net",
"41":"cthackereb@indiatimes.com",
"42":"dwilkensonj3@paginegialle.it",
"43":"tcleminshaw24@surveymonkey.com",
"44":"dseamansoc@rambler.ru",
"45":"friachgt@phpbb.com",
"46":"atesche6x@wordpress.com",
"47":"ppinkard2e@alexa.com",
"48":"dhowsleym0@spotify.com",
"49":"adecourcey8e@nymag.com",
"50":"omoraleseo@japanpost.jp",
"51":"speyzerc7@yellowbook.com",
"52":"hwhatfordpe@nba.com",
"53":"ccaldecuttjs@issuu.com",
"54":"jtimmiso4@clickbank.net",
"55":"ptrengovegi@cdbaby.com",
"56":"mgutch62@tinypic.com",
"57":"lflinders2c@tiny.cc",
"58":"sgrigore1h@phoca.cz",
"59":"tglentono8@unc.edu",
"60":"dkristofet@nifty.com",
"61":"jpearsejl@clickbank.net",
"62":"ljanatkam8@newsvine.com",
"63":"mgerlts4f@smugmug.com",
"64":"hmcenenyit@twitpic.com",
"65":"alegricedv@aol.com",
"66":"nleareqx@wikimedia.org",
"67":"mdunbabinj6@admin.ch",
"68":"tbarleybc@ibm.com",
"69":"aosgar69@who.int",
"70":"fcorkerpv@sbwire.com",
"71":"plisciandridl@sina.com.cn",
"72":"sdobell9c@youtube.com",
"73":"aderyebarrett2r@omniture.com",
"74":"cchildrenso3@china.com.cn",
"75":"bgemellich@blog.com",
"76":"jcolvilloi@arstechnica.com",
"77":"msnellre@addthis.com",
"78":"broakesaz@list-manage.com",
"79":"mrolingsonkz@cafepress.com",
"80":"ddudderidgeqo@illinois.edu",
"81":"nshenfischa6@surveymonkey.com",
"82":"knovotneig@ocn.ne.jp",
"83":"sstallybrasslv@businesswire.com",
"84":"ydeem2y@miitbeian.gov.cn",
"85":"fmandrycm@newsvine.com",
"86":"elaintonpf@goo.gl",
"87":"ahallgough6e@slashdot.org",
"88":"clodovichi1q@harvard.edu",
"89":"eohalligan7j@ox.ac.uk",
"90":"jmutchrk@wikia.com",
"91":"ederlpk@exblog.jp",
"92":"rbuck9i@wikispaces.com",
"93":"lcopyn93@nba.com",
"94":"iwinstanleyqh@google.co.uk",
"95":"vcucuzzajd@deviantart.com",
"96":"rgoeffdw@live.com",
"97":"vbohlmannk6@joomla.org",
"98":"ahradsky9q@ask.com",
"99":"bdeavels@prnewswire.com",
"100":"mharrigand5@livejournal.com",
"101":"edealygk@youku.com",
"102":"kbulcroftfz@microsoft.com",
"103":"drichienl@quantcast.com",
"104":"ehebbesiv@gov.uk",
"105":"cblinderma@thetimes.co.uk",
"106":"hmenaultdx@dyndns.org",
"107":"sallans6v@addtoany.com",
"108":"aellse2z@amazon.co.uk",
"109":"lpoonenq@xinhuanet.com",
"110":"rmateoso@friendfeed.com",
"111":"cfaynenx@xinhuanet.com",
"112":"atruderhu@list-manage.com",
"113":"ekeenq0@nsw.gov.au",
"114":"vstilldalebo@infoseek.co.jp",
"115":"fstickellsh9@ocn.ne.jp",
"116":"clefleya7@vinaora.com",
"117":"fkimbleno0@dell.com",
"118":"mlukasikok@google.nl",
"119":"nfoat41@nba.com",
"120":"hjergol@ow.ly",
"121":"wdigiorgioiy@tumblr.com",
"122":"nmeece42@netscape.com",
"123":"fmclevierf@prweb.com",
"124":"ncolgravelo@npr.org",
"125":"ntregenna7y@vimeo.com",
"126":"jworviell6f@yellowbook.com",
"127":"gunthankmk@posterous.com",
"128":"dpilipyakrh@berkeley.edu",
"129":"cstanionn0@myspace.com",
"130":"dwilkissonhv@opera.com",
"131":"zdonohoel2@shinystat.com",
"132":"gbrands4r@paypal.com",
"133":"bdelucaft@blogspot.com",
"134":"dhanburybrown98@devhub.com",
"135":"xmcdonoghk4@nba.com",
"136":"bgotcherh4@youku.com",
"137":"mwindressqj@yahoo.com",
"138":"olimbrick7o@google.de",
"139":"kbachmaneu@flickr.com",
"140":"aslowgrove33@biblegateway.com",
"141":"gcake1v@msu.edu",
"142":"bdenneslk@webs.com",
"143":"jhenrysda@ifeng.com",
"144":"cdufourfx@cdbaby.com"
}
}