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sudo wget -O /etc/apt/sources.list.d/bigtop-1.3.0.list http://archive.apache.org/dist/bigtop/bigtop-1.3.0/repos/ubuntu16.04/bigtop.list |
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wget -O- http://archive.apache.org/dist/bigtop/bigtop-1.3.0/repos/GPG-KEY-bigtop | sudo apt-key add - |
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import numpy as np | |
choice1_count = 0 | |
choice2_count = 0 | |
for i in range(0,7000000): | |
random_choice = random.SystemRandom() | |
choice = random_choice.choice([1,2]) | |
if choice == 1: | |
choice1_count += 1 | |
else: |
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{"modelTopology": {"keras_version": "2.1.6-tf", "backend": "tensorflow", "model_config": {"class_name": "Sequential", "config": {"name": "sequential_1", "layers": [{"class_name": "Conv2D", "config": {"name": "conv2d", "trainable": true, "batch_input_shape": [null, 28, 28, 1], "dtype": "float32", "filters": 16, "kernel_size": [5, 5], "strides": [2, 2], "padding": "valid", "data_format": "channels_last", "dilation_rate": [1, 1], "activation": "relu", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null, "dtype": "float32"}}, "bias_initializer": {"class_name": "Zeros", "config": {"dtype": "float32"}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}}, {"class_name": "MaxPooling2D", "config": {"name": "max_pooling2d", "trainable": true, "dtype": "float32", "pool_size": [2, 2], "padding": "valid", "strides": [2, 2], "data_format": "channels_last"}}, {"class_name": "Conv2D", "config": {" |
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degreesCount = g.degrees.count() | |
pr = g.pageRank(resetProbability = 0.15, tol=0.01) |
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from graphframes import * | |
vertices = sqlContext.createDataFrame(userIds, ["id"]) | |
edges = sqlContext.createDataFrame(edgesList, ["src", "dst", "relationship"]) | |
g = GraphFrame(vertices, edges) |
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import pymongo as pm | |
client = pm.MongoClient() | |
db = client.instagram | |
followerIds = db.followerIds | |
pipeline = [{"$unwind": "$follows"}] | |
relationships = list(followerIds.aggregate(pipeline)) | |
userIds = list(followerIds.aggregate([{"$match": {"follows": {"$exists": True}}},{"$project": {"_id": 1}}])) |
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db.followers.aggregate({$project: {_id: 1}}).forEach(function(obj){ | |
db.followerIds.insert(obj) | |
}) |
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def getFullListOfFollowers(userId): | |
fullFollowersList = [] | |
response = getFollowers(userId, '') | |
if response.get('data') == None: | |
print "Access denied" | |
return fullFollowersList | |
while(1): | |
fullFollowersList.extend(response.get('data')) |
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