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Showing posts with the label apache-storm-topology-example

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Top Questions People Ask About Pandas, NumPy, Matplotlib & Scikit-learn — Answered!

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 Whether you're a beginner or brushing up on your skills, these are the real-world questions Python learners ask most about key libraries in data science. Let’s dive in! 🐍 🐼 Pandas: Data Manipulation Made Easy 1. How do I handle missing data in a DataFrame? df.fillna( 0 ) # Replace NaNs with 0 df.dropna() # Remove rows with NaNs df.isna(). sum () # Count missing values per column 2. How can I merge or join two DataFrames? pd.merge(df1, df2, on= 'id' , how= 'inner' ) # inner, left, right, outer 3. What is the difference between loc[] and iloc[] ? loc[] uses labels (e.g., column names) iloc[] uses integer positions df.loc[ 0 , 'name' ] # label-based df.iloc[ 0 , 1 ] # index-based 4. How do I group data and perform aggregation? df.groupby( 'category' )[ 'sales' ]. sum () 5. How can I convert a column to datetime format? df[ 'date' ] = pd.to_datetime(df[ 'date' ]) ...

Apache Storm Architecture Tutorial Flowchart

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There are two main reasons why Apache Storm is so popular. The number one is it can connect to many sources. The number two is scalable. The other advantage is fault-tolerant. That means, guaranteed data processing. The map-reduce jobs process data analytics in Hadoop. The topology in Storm is the real data processor. The co-ordination between Nimbus and Supervisor carried by Zookeeper Apache Storm The jobs in Hadoop are similar to the topology. The jobs run as per the schedule defined. In Storm, the topology runs forever. A topology consists of many worker processes spread across many machines.  A topology is a pre-defined design to get end product using your data. A topology comprises of 2 parts. These are Spout and bolts. The Spout is a funnel for topology Two nodes in Storm Master Node: similar to the Hadoop job tracker. It runs on a daemon called Nimbus. Worker Node: It runs on a daemon called Supervisor. The Supervisor listens to the work assigne...