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Effective people
08/08/2022

Effective people

Common SQL Commands
08/08/2022

Common SQL Commands

Most common Apache spark use case1.PySpark – groupby with aggregation (count, sum, mean, min, max) https://www.freshers....
27/07/2022

Most common Apache spark use case
1.PySpark – groupby with aggregation (count, sum, mean, min, max)
https://www.freshers.in/uncategorized/pyspark-groupby-with-aggregation/
2.How to renaming Spark Dataframe having a complex schema with AWS Glue – PySpark
https://www.freshers.in/article/spark/renaming-spark-dataframe-having-a-complex-schema-in-aws-glue-pyspark/
3.PySpark – How to read a text file as RDD using Spark3 and Display the result in Windows 10
https://www.freshers.in/article/spark/pyspark-how-to-read-a-text-file-using-spark-windows-10/
4.PySpark how to get rows having nulls for a column or columns without nulls or count of Non null
https://www.freshers.in/article/spark/pyspark-how-to-get-rows-having-nulls-for-a-column-or-columns-without-nulls-or-count-of-non-null/
5.Converts a column containing a StructType, ArrayType or a MapType into a JSON string-PySpark(to_json)
https://www.freshers.in/article/spark/converts-a-column-containing-a-structtype-arraytype-or-a-maptype-into-a-json-string-using-pyspark-to_json/
6.How to get json object from a json string based on json path specified – get_json_object – PySpark
https://www.freshers.in/article/spark/how-to-get-json-object-from-a-json-string-get_json_object-pyspark/
7.How to round the given value to scale decimal places using HALF_EVEN rounding in Spark – PySpark
https://www.freshers.in/article/spark/how-to-round-the-given-value-to-scale-decimal-places-using-half_even-rounding-in-spark-pyspark/
8.How to replace a value with another value in a column in Pyspark Dataframe ?
https://www.freshers.in/article/spark/how-to-replace-a-value-with-another-value-in-a-column-in-pyspark-dataframe/
9.How to drop nulls in a dataframe : PySpark
https://www.freshers.in/article/spark/how-to-drop-nulls-in-a-dataframe-pyspark/
10.In Spark how to replace null value for all columns or for each column separately-PySpark (na.fill)
https://www.freshers.in/article/spark/in-spark-how-to-replace-null-value-for-all-columns-or-for-each-column-separately-pyspark/
11.How to create an array containing a column repeated count times – PySpark
https://www.freshers.in/article/spark/how-to-create-an-array-containing-a-column-repeated-count-times-pyspark/
12.How to run a Spark Job in Airflow hosted on a different server using BashOperator ?
https://www.freshers.in/article/spark/how-to-run-a-spark-job-in-airflow-hosted-on-a-different-server-using-bashoperator/
13.How to create UDF in PySpark ? What are the different ways you can call PySpark UDF ( With example)
https://www.freshers.in/article/spark/how-to-create-udf-in-pyspark-what-are-the-different-ways-you-can-call-pyspark-udf-with-example/
14.How to convert MapType to multiple columns based on Key using PySpark ?
https://www.freshers.in/article/spark/how-to-convert-maptype-to-multiple-columns-based-on-key-using-pyspark/
15.What is the difference between concat and concat_ws in Pyspark
https://www.freshers.in/article/spark/difference-between-concat-and-concat_ws-in-pyspark/
16.How to add a new column in PySpark using withColumn
https://www.freshers.in/article/spark/how-to-add-a-new-column-in-pyspark-using-withcolumn/
17.How to use filter or where condition in PySpark
https://www.freshers.in/article/spark/how-to-use-filter-or-where-condition-in-pyspark/
18.Explain Complex datatype PySpark (ArrayType,MapType,StructType)
https://www.freshers.in/article/spark/explain-complex-datatype-pyspark-arraytype-maptype-structtype/
19.How to create tables from Spark Dataframe and join the tables (createOrReplaceTempView)
https://www.freshers.in/article/spark/how-to-create-tables-from-spark-dataframe-and-join-the-tables-createorreplacetempview/
20.How to transform a JSON Column to multiple columns based on Key in PySpark
https://www.freshers.in/article/spark/how-to-transform-a-json-column-to-multiple-columns-based-on-key-in-pyspark/
21.How to parses a column containing a JSON string using PySpark(from_json)
https://www.freshers.in/article/spark/how-to-parses-a-column-containing-a-json-string-using-pyspark-from_json/
22.How to get the common elements from two arrays in two columns in PySpark (array_intersect)
https://www.freshers.in/article/spark/how-to-get-the-common-elements-from-two-arrays-in-two-columns-in-pyspark-array_intersect/
23.How to find difference between two arrays in PySpark(array_except)
https://www.freshers.in/article/spark/how-to-find-difference-between-two-arrays-in-pysparkarray_except/
24.How to convert Array elements to Rows in PySpark ? PySpark – Explode Example code.
https://www.freshers.in/article/spark/how-to-convert-array-elements-to-rows-in-pyspark-explode-example-code/
25.How to find array contains a given value or values using PySpark ( PySpark search in array)
https://www.freshers.in/article/spark/how-to-find-array-contains-a-given-value-or-values-using-pyspark-pyspark-search-in-array/

15/09/2020

Spark 3 has been released with major improvements in Python and SQL support. Spark is the general-purpose cluster computing framework that has native support for distributed SQL and enables streaming, graph processing, and machine learning.

05/06/2017

How to avoid seven common Hadoop mistakes
==========================================
Mistake 1: Migrate everything before devising a plan
Mistake 2: Assume rational database skillsets are transferable to Hadoop
Mistake 3: Treating a Hadoop data lake like a regular database
Mistake 4: I can figure out security later
Mistake 5: Common strategic mistakes
Mistake 6: Bridging the skills gap with traditional ETL
Mistake 7: I can get enterprise-level value on a small budget

Source : http://www.itproportal.com/features/how-to-avoid-seven-common-hadoop-mistakes/

22/12/2016

How to control log messages in SPARK - LogLevel
------------------------------------------
Control your logLevel. This will override any user defined log settings. Valid log levels include: ALL, DEBUG, ERROR, FATAL, INFO, OFF, TRACE, WARN
Get the code at :
http://www.wikihadoop.com/2016/12/how-to-control-log-messages-in-spark.html

Control your logLevel. This will override any user defined log settings. Valid log levels include: ALL, DEBUG, ERROR, FATAL, INFO, OFF, TRA...

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