About Google Certified Professional – Data Engineer
A Professional Data Engineer gathers, transforms, and publishes data to make data-driven decisions. With security and compliance, scalability and efficiency, fidelity and dependability, adaptability, and portability in mind, a data engineer should be able to design, construct, operationalize, secure, and monitor data processing systems.
Google Certified Professional – Data Engineer Interview Questions & Answers
Explain the concept of data engineering.
In the field of big data, the word “data engineering” is used. It concentrates on the use of data collection and analysis. The information gathered from different sources is merely raw information. Data engineering aids in the transformation of unusable data into valuable knowledge.
What is the concept of data modelling?
Data modeling is a technique for visually recording complex software designs in a way that everyone can understand. It is a conceptual representation of data objects that are linked to laws and other data objects.
When Block Scanner detects a compromised data block, what happens next?
When Block Scanner detects a compromised data block, the following steps occur:
- First and foremost, when the Block Scanner detects a compromised data block, DataNode notifies NameNode.
- NameNode begins the process of constructing a new replica from a corrupted block replica.
- The replication factor is compared to the replication count of the right replicas. The compromised data block will not be removed if a match is found.
How do you go about deploying a big data solution?
To deploy a big data solution, go through the steps below.
- Combine data from various sources such as RDBMS, SAP, MySQL, and Salesforce.
- Save the data extracted in a NoSQL database or HDFS.
- Use computing frameworks like Pig, Spark, and MapReduce to deploy a big data solution.
When it comes to Data Modeling, what are some of the architecture schemas that are used?
When it comes to data modelling, there are two schemas to consider. They are as follows:
- Star schema
- Snowflake schema
What makes structured data different from unstructured data?
| Parameters | Structured Data | Unstructured Data |
| Storage Method | DBMS | Most of it unmanaged |
| Protocol Standards | ODBC, SQL, and ADO.NET | XML, CSV, SMSM, and SMTP |
| Scaling | Schema scaling is difficult | Schema scaling is very easy |
| Example | An ordered text dataset file | Images, videos, etc. |
In a nutshell, what is Star Schema?
The star schema, also known as the star join schema, is one of the most basic schemas in the Data Warehousing definition. It has a star-like structure, with fact tables and related dimension tables. When dealing with large quantities of data, use the star schema.
What is Snowflake Schema, in brief?
With the addition of more dimensions, the snowflake schema is a primary extension of the star schema. The name comes from the fact that it is shaped like a snowflake. After normalisation, the data is ordered and divided into more tables.
What are some of the methods of Reducer()?
The three main methods of reducer:
- setup(): This primarily configures input data parameters and cache protocols.
- cleanup(): This method removes the temporary files stored.
- reduce(): The method is called one time for every key, and it happens to be the single most important aspect of the reducer on the whole.
What do you think a Data Engineer’s main responsibilities are?
A Data Engineer is in charge of a variety of tasks. Here are a few of the most important:
- Pipelines for data inflow and processing
- Keeping data staging areas up to date
- ETL data transformation activities are my responsibility.
- Doing data cleansing and redundancy elimination
- Creating native data extraction methods and ad-hoc query construction operations
What are some of the technologies and skills required of a Data Engineer?
The following are the main technologies that a Data Engineer should be familiar with:
- Mathematics (probability and linear algebra)
- Summary statistics
- Machine Learning
- R and SAS programming languages
- Python
- SQL and HiveQL
What does Rack Knowledge imply?
The NameNode utilizes the DataNode to enhance incoming network traffic while simultaneously reading or writing to the file that is closest to the rack from which the request was made, which refers to as rack knowledge.
What is Metastore’s purpose in Hive?
For the schema and Hive tables, Metastore is used as a storage site. The metastore can store data such as descriptions, mappings, and other metadata. This information is later stored in an RDMS as required.
What are the different components in the Hive data model?
Following are some of the components in Hive:
- Buckets
- Tables
- Partitions
Is it possible to make more than one table for a single data file?
Yes, several tables can be created for a single data file. Schemas are contained in Hive’s metastore. As a consequence, obtaining the result for the corresponding data is very easy.
List various complex data types/collection are supported by Hive
Hive supports the following complex data types:
- Map
- Struct
- Array
- Union
In Hive, what is SerDe?
- Serialization and Deserialization in Hive are referred to as SerDe. It is the operation that occurs as records and then passes through Hive tables.
- The Deserializer takes a record and transforms it into a Hive-compatible Java object.
- The Serializer now takes this Java object and transforms it into an HDFS-compatible format. HDFS takes over the storage role later.
Explain how .hiverc file in Hive is used?
In Hive, .hiverc is the initialization file. When we start Hive’s Command Line Interface (CLI), this file is loaded first. We can set the initial values of parameters in .hiverc file.
Is it possible to create more than one table in Hive for a single data file?
Yes, we can have many table schemas for the same data file. In Hive Metastore, Hive saves schema. We may get different outputs from the same data using this design.
Explain different SerDe implementations available in Hive
In Hive, there are several SerDe implementations. You may even create your own SerDe implementation from scratch. Here are a few well-known SerDe implementations:
- OpenCSVSerde
- RegexSerDe
- DelimitedJSONSerDe
- ByteStreamTypedSerDe
List out objects created by create statement in MySQL.
Objects created by create statement in MySQL are as follows:
- Database
- Index
- Table
- User
- Procedure
- Trigger
- Event
- View
- Function
How to see the database structure in MySQL?
In order to see database structure in MySQL, you can use
DESCRIBE command. Syntax of this command is DESCRIBE Table name;.
What is the difference between a Data Warehouse and a Database, in a nutshell?
When it comes to Data Warehousing, the main emphasis is on using aggregation functions, conducting calculations, and choosing data subsets for processing. The primary use of databases is for data manipulation, deletion, and other similar tasks. When dealing with any of these, speed and reliability are crucial.
24. What are the functions of Secondary NameNode?
Following are the functions of Secondary NameNode:
- FsImage which stores a copy of EditLog and FsImage file.
- NameNode crash: If the NameNode crashes, then Secondary NameNode’s FsImage can be used to recreate the NameNode.
- Checkpoint: It is used by Secondary NameNode to confirm that data is not corrupted in HDFS.
- Update: It automatically updates the EditLog and FsImage file. It helps to keep FsImage file on Secondary NameNode updated
25. What do you mean by Rack Awareness?
In Haddop cluster, Namenode uses the Datanode to improve the network traffic while reading or writing any file that is closer to the nearby rack to Read or Write request. To obtain rack information, Namenode keeps track of each DataNode’s rack id. In Hadoop, this idea refers to as Rack Awareness.
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