Unsupported Data Storage Formats

Correct Answers: C, H and I

Spark offers several options for storing the data in the managed tables, such as TEXT, JSON, CSV, JDBC, ORC, PARQUET, DELTA, LIBSVM and HIVE.

These files are typically saved in the warehouse directory where data for the managed table is stored.

Option A is incorrect.

Spark supports TEXT format.

Option B is incorrect.

Spark supports CSV format.

Option C is correct.

XML format is not supported by Spark.

Option D is incorrect.

Spark supports JSON format.

Option E is incorrect.

JDBC format is supported by Spark.

Option F is incorrect.

PARQUET format is supported by Spark.

Option G is incorrect.

Spark supports LIBSVM format.

Option H is correct.

Spark does not support MPV4 format for data storage.

Option I is correct.

Spark does not support a Binary format for data storage.

To know more about Spark created tables, please visit the below-given link:

Spark supports several data storage formats for managed tables, which are tables whose schema and data are managed by Spark. These formats include TEXT, CSV, XML, JSON, JDBC, PARQUET, and LIBSVM. However, Spark does not support the BINARY and MPV4 formats for managed tables.

Here is a brief overview of the supported and unsupported formats for Spark managed tables:

Supported Formats:

1. TEXT: Spark can read and write text files, which contain records separated by a delimiter, such as a comma or tab.

2. CSV: Spark can read and write CSV files, which are similar to text files but have a well-defined structure that includes a header row and columns separated by commas.

3. XML: Spark can read and write XML files, which use tags to define the structure of the data.

4. JSON: Spark can read and write JSON files, which are a common data format used in web applications.

5. JDBC: Spark can read and write data from relational databases using JDBC.

6. PARQUET: Spark can read and write Parquet files, which are a columnar storage format that is optimized for analytics workloads.

7. LIBSVM: Spark can read and write LIBSVM files, which are a text-based format for representing sparse datasets used in machine learning.

Unsupported Formats:

1. BINARY: Spark does not support binary files for managed tables. Binary files are files that contain non-textual data, such as images or executables.

2. MPV4: Spark does not support MPV4 files for managed tables. MPV4 is a video compression format.

In summary, Spark supports a wide range of data storage formats for managed tables, including text, CSV, XML, JSON, JDBC, Parquet, and LIBSVM. However, it does not support binary files or MPV4 files for managed tables.