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# A simple cheat sheet of Spark Dataframe syntax | |
# Current for Spark 1.6.1 | |
# import statements | |
from pyspark.sql import SQLContext | |
from pyspark.sql.types import * | |
from pyspark.sql.functions import * | |
#creating dataframes | |
df = sqlContext.createDataFrame([(1, 4), (2, 5), (3, 6)], ["A", "B"]) # from manual data |
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val s3Paths = "s3://yourbucket/path/to/file1.txt,s3://yourbucket/path/to/directory" | |
val pageLength = 100 | |
val key = "YOURKEY" | |
val secret = "YOUR_SECRET" | |
import com.amazonaws.services.s3._, model._ | |
import com.amazonaws.auth.BasicAWSCredentials | |
import com.amazonaws.services.s3.model.ObjectListing | |
import scala.collection.JavaConverters._ | |
import scala.io.Source |
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curl -XPOST http://localhost:9200/test/articles/1 -d '{ | |
"content": "The quick brown fox" | |
}' | |
curl -XPOST http://localhost:9200/test/articles/2 -d '{ | |
"content": "What does the fox say?" | |
}' | |
curl -XPOST http://localhost:9200/test/articles/3 -d '{ | |
"content": "The quick brown fox jumped over the lazy dog" | |
}' | |
curl -XPOST http://localhost:9200/test/articles/4 -d '{ |
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import redis | |
import threading | |
class Listener(threading.Thread): | |
def __init__(self, r, channels): | |
threading.Thread.__init__(self) | |
self.redis = r | |
self.pubsub = self.redis.pubsub() | |
self.pubsub.subscribe(channels) | |