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Showing posts with the label Hadoop Utilities

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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' ]) ...
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Hadoop: How to find which file is healthy

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Hadoop provides file system health check utility which is called "fsck". Basically, it checks the health of all the files under a path It also checks the health of all the files under the '/'(root). BIN/HADOOP fsck / - It checks the health of all the files BIN/HADOOP fsck /test/ - It checks the health of files under the path By default fsck utility cannot do anything for under replicated blocks and over replicated blocks. Hadoop itself heal the blocks.   How to find which file is healthy It prints out dot for each healthy file It will print a message for each file, if it is not healthy, also for under replicated blocks, over replicated blocks, mis-replicated blocks, and corrupted blocks. By default fsck utility cannot do anything for under replicated blocks and over replicated blocks. Hadoop itself heal the blocks. How to delete corrupted blocks BIN/HADOOP fsck -delete block-names It will delete all corrupted blocks BIN/HADOOP fsck -m...
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