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ARA-C01 SnowPro Advanced Architect Certification Exam

  • Snowflake
  • 5 free sample questions

About this exam

ARA-C01 is the Snowflake exam SnowPro Advanced Architect Certification Exam. Paid practice material for this exam is not available yet, but you can try its free sample questions.

Exam code
ARA-C01
Vendor
Snowflake
Practice questions
Not available yet
Free sample questions
5
Question bank last updated
Not available yet

Try 2 sample questions

Taken from the free sample set for ARA-C01.

Question 1

Which technique will efficiently ingest and consume semi-structured data for Snowflake data lake workloads?

  1. Option A:

    IDEF1X

  2. Option B:

    Schema-on-write

  3. Option C:

    Schema-on-read

  4. Option D:

    Information schema

Show answer and explanation

Correct answer: C

Option C is the correct answer because schema-on-read is a technique that allows Snowflake to ingest and consume semi-structured data without requiring a predefined schema. Snowflake supports various semi-structured data formats such as JSON, Avro, ORC, Parquet, and XML, and provides native data types (ARRAY, OBJECT, and VARIANT) for storing them. Snowflake also provides native support for querying semi-structured data using SQL and dot notation. Schema-on-read enables Snowflake to query semi-structured data at the same speed as performing relational queries while preserving the flexibility of schema-on-read. Snowflake’s near-instant elasticity rightsizes compute resources, and consumption-based pricing ensures you only pay for what you use.

Option A is incorrect because IDEF1X is a data modeling technique that defines the structure and constraints of relational data using diagrams and notations. IDEF1X is not suitable for ingesting and consuming semi-structured data, which does not have a fixed schema or structure.

Option B is incorrect because schema-on-write is a technique that requires defining a schema before loading and processing data. Schema-on-write is not efficient for ingesting and consuming semi-structured data, which may have varying or complex structures that are difficult to fit into a predefined schema. Schema-on-write also introduces additional overhead and complexity for data transformation and validation.

Option D is incorrect because information schema is a set of metadata views that provide information about the objects and privileges in a Snowflake database. Information schema is not a technique for ingesting and consuming semi-structured data, but rather a way of accessing metadata about the data.

[References:, Semi-structured Data, Snowflake for Data Lake, , , , , ]

Question 2

A new table and streams are created with the following commands:


CREATE OR REPLACE TABLE LETTERS (ID INT, LETTER STRING) ;


CREATE OR REPLACE STREAM STREAM_1 ON TABLE LETTERS;


CREATE OR REPLACE STREAM STREAM_2 ON TABLE LETTERS APPEND_ONLY = TRUE;


The following operations are processed on the newly created table:


INSERT INTO LETTERS VALUES (1, ' A ' );


INSERT INTO LETTERS VALUES (2, ' B ' );


INSERT INTO LETTERS VALUES (3, ' C ' );


TRUNCATE TABLE LETTERS;


INSERT INTO LETTERS VALUES (4, ' D ' );


INSERT INTO LETTERS VALUES (5, ' E ' );


INSERT INTO LETTERS VALUES (6, ' F ' );


DELETE FROM LETTERS WHERE ID = 6;


What would be the output of the following SQL commands, in order?


SELECT COUNT (*) FROM STREAM_1;


SELECT COUNT (*) FROM STREAM_2;


  1. Option A:

    2 & 6

  2. Option B:

    2 & 3

  3. Option C:

    4 & 3

  4. Option D:

    4 & 6

Show answer and explanation

Correct answer: C

In Snowflake, a stream records data manipulation language (DML) changes to its base table since the stream was created or last consumed. STREAM_1 will show all changes including the TRUNCATE operation, while STREAM_2, being APPEND_ONLY, will not show deletions like TRUNCATE. Therefore, STREAM_1 will count the three inserts, the TRUNCATE (counted as a single operation), and the subsequent two inserts before the delete, totaling 4. STREAM_2 will only count the three initial inserts and the two after the TRUNCATE, totaling 3, as it does not count the TRUNCATE or the delete operation.

[References: The explanation is based on the Snowflake documentation on streams, which details how streams track changes and the difference between standard and APPEND_ONLY streams12., , , , , , ]
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