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8 Ways to Optimize AWS Glue Jobs in a Nutshell

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  Improving the performance of AWS Glue jobs involves several strategies that target different aspects of the ETL (Extract, Transform, Load) process. Here are some key practices. 1. Optimize Job Scripts Partitioning : Ensure your data is properly partitioned. Partitioning divides your data into manageable chunks, allowing parallel processing and reducing the amount of data scanned. Filtering : Apply pushdown predicates to filter data early in the ETL process, reducing the amount of data processed downstream. Compression : Use compressed file formats (e.g., Parquet, ORC) for your data sources and sinks. These formats not only reduce storage costs but also improve I/O performance. Optimize Transformations : Minimize the number of transformations and actions in your script. Combine transformations where possible and use DataFrame APIs which are optimized for performance. 2. Use Appropriate Data Formats Parquet and ORC : These columnar formats are efficient for storage and querying, signif

Big Data: Top Hadoop Interview Questions (4 of 5)

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1) What is MAP Reduce program? - You need to give actual steps in this program - You have to write scripts and codes 2) What is MAPReduce? -Mapreduce is a data processing model -It is combination of 2 parts. One is Mappers and the other one is Reducers 3)What will happen in Mapping phase? It takes the input data, and feeds each data element into the mapper 4)What is the function of Reducer? The reducer process all outputs from mapper and arrives at a final result 5)What kind of input required for Mapreduce? It should be structured in the form of (Key,Value) pairs 6)What is HDFS? HDFS is a file system designed for large-scale data processing under frameworks such as MapReduce. 7) Is HDFS like UNIX? No, but commands in HDFS works similarly to UNIX 8) What is Simple file command? hadoop fs -ls 9) How to copy data into HDFS file system? Copy a file into HDFS from local system 10) What is default working directory in HDFS? /user/$USER $USER ==> Your log