Data Engineering Data Serialization Formats 2

Question 1

Which encoding technique does Parquet use for columns with few distinct values (low cardinality)?

Accepted Answer

Dictionary encoding

Answer

Dictionary encoding replaces repeated values with integer references to a small dictionary, which is highly effective for low-cardinality columns where the same values appear many times.

Question 2

What is the primary benefit of reading columnar formats like Parquet in analytical query engines?

Accepted Answer

Only relevant columns are read from disk, reducing I/O significantly

Answer

Columnar storage allows query engines to read only the columns they need and skip all others on disk, dramatically reducing I/O and speeding up analytical queries.

Question 3

Which serialization format is most widely used for data interchange with REST APIs?

Accepted Answer

JSON

Answer

JSON is the de facto standard for REST API data interchange due to its human-readable nature, wide language support, and native compatibility with web technologies.

Question 4

What is Protocol Buffers (protobuf) primarily designed for?

Accepted Answer

Efficient binary serialization for structured data across languages

Answer

Protocol Buffers is Google's binary serialization format designed for efficient, language-neutral structured data serialization with small payload size and fast parsing.

Question 5

Which Parquet feature allows query engines to skip entire row groups based on filter conditions without reading the data?

Accepted Answer

Row group filtering using min/max statistics

Answer

Parquet stores min/max statistics for each row group and column chunk, allowing query engines to skip entire row groups when filter conditions cannot match any row in that group.

Data Engineering Practice Test

Data Engineering Practice Test

Data Engineering Data Serialization Formats 2