Final answer:
CSV and Avro are the two row-based data encoding formats among the options. CSV is a text-based format where records are separated by lines, and Avro is a binary format suitable for efficiently serializing data. ORC and Parquet, in contrast, are column-based formats optimized for analytical workloads.
Step-by-step explanation:
Among the options provided, CSV (D) and Avro (C) are the two data encoding formats that are based on a row-oriented approach. CSV is a simple, text-based format where each line represents a single record with values separated by a delimiter, typically a comma. This format is inherently row-based, as each row in the file corresponds to a single record. Avro, on the other hand, is a binary row-based format developed as part of the Apache Hadoop project and is designed for serializing data in a compact and efficient manner.
While ORC (A) and Parquet (B) are also data encoding formats, they follow a columnar storage approach. This means that they store data tables by column rather than by row, which facilitates efficient data compression and encoding schemes, especially for complex nested data structures. Their column-oriented design is suited for analytic workloads that typically involve reading a subset of columns from the dataset.