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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
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Top Hive interview Questions for quick read (1 of 2)

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The selected interview questions on HIVE. Hive is a technology being used in Hadoop eco system.

 1) What are major activities in Hadoop eco system?
Within the Hadoop ecosystem, HDFS can load and store massive quantities of data in an efficient and reliable manner. It can also serve that same data back up to client applications, such as MapReduce jobs, for processing and data analysis.
 2)What is the role of HIVE in HADOOP Eco system?
Hive, often considered the Hadoop data warehouse platform, got its start at Facebook as their analyst struggled to deal with the massive quantities of data produced by the social network. Requiring analysts to learn and write MapReduce jobs was neither productive nor practical.
Hive Questions
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3)What is Hive in Hadoop?
Facebook developed a data warehouse-like layer of abstraction that would be based on tables. The tables function merely as metadata, and the table schema is projected onto the data, instead of actually moving potentially massive sets of data. 

This new capability allowed their analyst to use a SQL-like language called Hive Query Language (HQL) to query massive data sets stored with HDFS and to perform both simple and sophisticated summarizations and data analysis.

4)What is the requirement for HIVE learning?
If you are familiar with basic T-SQL data definition language (DDL) commands, you already have a good head start in working with Hive tables.

5)What is CREATE Table in HIVE?
CREATE EXTERNAL TABLE iislogtest (
       date STRING,
       time STRING,
       username STRING,
       ip STRING,
       port INT,
       method STRING,
       uristem STRING,
       uriquery STRING,
       timetaken INT,
       useragent STRING,
       referrer STRING
)
ROW FORMAT DELIMITED FIELDS TERMINATED BY ',';

6) What is SELECT statement in Query?
SELECT *
FROM iislogtest; 
This simple query, simply returns all rows found in the iislogtest table.

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