10+ Abinitio Developer Interview Questions and Answers

Output index is a single index while output indexes is an array of indexes in Reformat component.

• Output index refers to a single output field in Reformat component.

• Output indexes refer to multiple output fields in Reformat component.

• Output index is specified using a single integer value.

• Output indexes are specified using an array of integer values.

Use UNPIVOT operator in SQL to convert a column into a row.

• Use UNPIVOT operator in SQL to convert a column into a row

• Syntax: SELECT * FROM (SELECT [column_name] FROM [table_name]) AS [alias_name] UNPIVOT ([new_column_name] FOR [old_column_name] IN ([column_name])) AS [alias_name]

• Example: SELECT * FROM (SELECT col1, col2, col3 FROM table1) AS t UNPIVOT (val FOR col IN (col1, col2, col3)) AS u

• Transpose function in Excel can also be used to convert a column into a row

Partitioning divides a table into smaller parts while bucketing groups data based on a hash function.

• Partitioning is used to improve query performance by reducing the amount of data that needs to be scanned.

• Bucketing is used to evenly distribute data across nodes in a cluster.

• Partitioning is done based on a column or set of columns, while bucketing is done based on a hash function.

• Partitioning is commonly used in databases like Oracle and MySQL, while bucketing is commonly us...read more

The output of a rollup component with {} key on an MFS file will be the aggregated values based on the specified key.

• The rollup component in Abinitio is used to perform aggregation operations on data.

• The {} key in the rollup component indicates that all records should be considered for aggregation.

• The output will contain the aggregated values based on the specified key.

• For example, if the MFS file contains student records with roll numbers as the key, the output will provide ...read more

Use the GROUP BY clause with HAVING to find duplicates in SQL.

• Use the GROUP BY clause to group rows with the same values together

• Use the HAVING clause to filter out groups that have more than one row (indicating duplicates)

• Example: SELECT column_name, COUNT(*) FROM table_name GROUP BY column_name HAVING COUNT(*) > 1;

Yes, I have worked on procedures in Abinitio development.

• I have experience creating and implementing procedures in Abinitio to automate data processing tasks.

• I have written complex procedures using Abinitio's graphical interface or scripting language.

• I have optimized procedures for performance and efficiency.

• I have debugged and troubleshooted procedures to ensure they function correctly.

• I have documented procedures for future reference and maintenance.

Normalize component is used in Abinitio to standardize and transform data into a consistent format.

• Normalize component is used to remove redundancy and inconsistencies in data.

• It helps in transforming data into a consistent format by applying rules and transformations.

• Normalization can involve splitting data into multiple tables, removing duplicate records, or standardizing values.

• Example: Normalizing a customer database by splitting it into separate tables for customers, ord...read more

Fact and dimension are two types of data in a data warehouse.

• Fact: Represents the measurable and numerical data in a data warehouse.

• Dimension: Represents the descriptive attributes of the data in a data warehouse.

• Fact tables contain foreign keys to dimension tables.

• Example: In a sales data warehouse, the fact table may contain sales amount, quantity sold, and date, while the dimension table may contain product, customer, and location details.

Abinitio components are building blocks used for data processing in Abinitio applications.

• Components are reusable building blocks for data processing tasks.

• They can be used for data extraction, transformation, and loading.

• Examples of components include Reformat, Sort, Join, and Partition.

• Components can be combined to create complex data processing workflows.

A JOIN is used to combine rows from two or more tables based on a related column between them.

• Types of JOINs include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.

• INNER JOIN returns rows when there is at least one match in both tables.

• LEFT JOIN returns all rows from the left table and the matched rows from the right table.

• RIGHT JOIN returns all rows from the right table and the matched rows from the left table.

• FULL JOIN returns rows when there is a match in one of the tabl...read more