i
Cognizant
Proud winner of ABECA 2024 - AmbitionBox Employee Choice Awards
Filter interviews by
Deleting duplicate rows in SQL
Use the DISTINCT keyword in SELECT statement to retrieve unique rows
Use GROUP BY clause to group rows with same values and then use aggregate functions to select one row
Use the ROW_NUMBER() function to assign a unique number to each row and then delete the rows with duplicate numbers
To remove header and trailer from a sequential data file in Datastage.
Use Sequential File stage in Datastage.
Set the 'Skip Rows' property to the number of header rows to be skipped.
Set the 'Trailer Rows' property to the number of trailer rows to be skipped.
Use a Transformer stage to remove any remaining header or trailer rows.
Use the 'Remove' function in the Transformer stage to remove the rows.
To kill a job in Datastage
Stop the job manually from the Director client
Terminate the job from the command line using the dsjob command
Kill the job process from the operating system level
Delete the job from the Datastage repository
To find process id in Linux, use the command 'ps -aux | grep
Open the terminal
Type 'ps -aux' to list all running processes
Use 'grep
The process id (PID) will be listed in the second column
SQL queries with window functions
Window functions perform calculations across a set of rows that are related to the current row
Common window functions include ROW_NUMBER, RANK, DENSE_RANK, and NTILE
Window functions are used with the OVER() clause to define the window or subset of rows to perform the calculation on
SORT BY, ORDER BY, CLUSTER BY, and DISTRIBUTE BY are SQL clauses used for data sorting and partitioning.
SORT BY is used to sort the result set in ascending or descending order based on one or more columns.
ORDER BY is used to sort the result set in ascending or descending order based on one or more columns. It is similar to SORT BY but can be used with other clauses like LIMIT and OFFSET.
CLUSTER BY is used to group data...
Small file problem refers to the issue of having a large number of small files in a storage system.
Small files can cause inefficiencies in storage and processing.
Solutions include consolidating small files into larger ones or using a different storage system.
Examples include Hadoop's SequenceFile format and Amazon S3's object size optimization.
RDS, VA, DF, VS, and DS are all acronyms related to data engineering.
RDS stands for Relational Database Service, a managed database service by AWS.
VA stands for Virtual Assistant, a software program that can assist with tasks.
DF stands for Dataflow, a managed service by Google Cloud for data processing.
VS stands for Virtual Server, a server that runs on a virtual machine.
DS stands for Datastore, a NoSQL document databa
I applied via Recruitment Consultant and was interviewed in Sep 2021. There were 3 interview rounds.
What people are saying about Cognizant
I applied via Recruitment Consultant and was interviewed before Jun 2020. There were 4 interview rounds.
Reading data from a .log file and extracting columns with a specific regex.
Use Python's built-in 're' module to define the regex pattern.
Open the .log file using Python's 'open' function.
Iterate through each line of the file and extract the desired columns using the regex pattern.
Store the extracted data in a data structure such as a list or dictionary.
Optimizations for data engineering
Use indexing to speed up queries
Partition data to improve query performance
Use caching to reduce data retrieval time
Optimize data storage format for faster processing
Use parallel processing to speed up data processing
Optimize network bandwidth usage
Use compression to reduce storage and network usage
Answering how to read JSON in Python.
Use the json module to load and parse JSON data
Use the json.loads() method to load JSON data from a string
Use the json.load() method to load JSON data from a file
Access JSON data using keys or indexes
Use the json.dumps() method to convert Python objects to JSON strings
Pyspark configs
Pyspark configs are used to configure the behavior of a Pyspark application.
They can be set using SparkConf object or spark-submit command.
Examples include setting the number of executors, memory allocation, and log level.
Cognizant interview questions for designations
I applied via Campus Placement and was interviewed before Feb 2020. There were 4 interview rounds.
I applied via Campus Placement and was interviewed in Mar 2020. There was 1 interview round.
To get the second to last element from a SQL table, use the OFFSET-FETCH clause.
Use the ORDER BY clause to sort the table in descending order.
Use the OFFSET-FETCH clause to skip the last row and fetch the second to last row.
Example: SELECT column_name FROM table_name ORDER BY column_name DESC OFFSET 1 ROWS FETCH NEXT 1 ROWS ONLY;
I applied via Campus Placement and was interviewed before May 2020. There were 3 interview rounds.
I applied via Campus Placement and was interviewed before Mar 2020. There were 3 interview rounds.
I applied via Campus Placement and was interviewed before Mar 2020. There was 1 interview round.
Triggers are database objects that automatically execute in response to certain events or changes in data.
Triggers are used to enforce business rules or data integrity.
They can be used to audit changes to data.
Triggers can be set to execute before or after an event, such as an insert, update, or delete operation.
They can be defined on tables, views, or schemas.
Examples of triggers include sending an email notification ...
based on 5 reviews
Rating in categories
Associate
72.2k
salaries
| ₹5.2 L/yr - ₹16 L/yr |
Programmer Analyst
55.6k
salaries
| ₹2.4 L/yr - ₹9.4 L/yr |
Senior Associate
49.5k
salaries
| ₹8.9 L/yr - ₹28 L/yr |
Senior Processing Executive
29k
salaries
| ₹1.8 L/yr - ₹9 L/yr |
Technical Lead
17.6k
salaries
| ₹5.9 L/yr - ₹25 L/yr |
TCS
Infosys
Wipro
Accenture