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Exam Certified Data Engineer Professional topic 1 question 14 discussion

Actual exam question from Databricks's Certified Data Engineer Professional

Question #: 14
Topic #: 1

[All Certified Data Engineer Professional Questions]

An hourly batch job is configured to ingest data files from a cloud object storage container where each batch represent all records produced by the source system in a given hour. The batch job to process these records into the Lakehouse is sufficiently delayed to ensure no late-arriving data is missed. The user_id field represents a unique key for the data, which has the following schema: user_id BIGINT, username STRING, user_utc STRING, user_region STRING, last_login BIGINT, auto_pay BOOLEAN, last_updated BIGINT
New records are all ingested into a table named account_history which maintains a full record of all data in the same schema as the source. The next table in the system is named account_current and is implemented as a Type 1 table representing the most recent value for each unique user_id.
Assuming there are millions of user accounts and tens of thousands of records processed hourly, which implementation can be used to efficiently update the described account_current table as part of each hourly batch job?

A. Use Auto Loader to subscribe to new files in the account_history directory; configure a Structured Streaming trigger once job to batch update newly detected files into the account_current table.
B. Overwrite the account_current table with each batch using the results of a query against the account_history table grouping by user_id and filtering for the max value of last_updated.
C. Filter records in account_history using the last_updated field and the most recent hour processed, as well as the max last_iogin by user_id write a merge statement to update or insert the most recent value for each user_id.
D. Use Delta Lake version history to get the difference between the latest version of account_history and one version prior, then write these records to account_current.
E. Filter records in account_history using the last_updated field and the most recent hour processed, making sure to deduplicate on username; write a merge statement to update or insert the most recent value for each username.

Show Suggested Answer

Suggested Answer: C 🗳️

by thxsgod at Sept. 7, 2023, 12:35 p.m.

Comments

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RafaelCFC

Highly Voted 1 year, 6 months ago

Selected Answer: C

My reasoning is thus: The application is based on batch processes, so A is wrong. Overwriting the table would destroy the Type 1 SCD behavior, so B is wrong. Comparing versions of account_history would not be efficient, as the whole data would be scanned, so D is wrong. 'username' is not a key column, so we have no guarantee that it's unique, thus de-duplicating by it can yield wrongly grouped sets of rows, so E is not a safe bet, with the information we know. C is the best option.

upvoted 11 times

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terrku

Highly Voted 1 year, 3 months ago

Selected Answer: B

Type 1 table means the behavior is overwriting.

upvoted 9 times

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363c4c5

Most Recent 5 days, 9 hours ago

Selected Answer: C

It depends on whether we receive the full list of user accounts each time. It says: "each batch represents all records produced by the source system in a given hour", so if we use option B, we might miss some accounts.

upvoted 2 times

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thotwielder

1 month ago

Selected Answer: B

c: wrong. it is using last_login, but the key is user_id, no reason to group by last_login. b: correct. group by key (user_id), and get the latest record. overwrite is very efficient.

upvoted 2 times

thotwielder

1 month ago

update. to clarify c is wrong not because group by last_login. c is wrong because merge is not as efficient as overwrite because there are millions of user which means the accout_current table is huge and merge needs to compare source and target table which is time consuming compared with simple overwrite.

upvoted 1 times

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KadELbied

2 months, 1 week ago

Selected Answer: C

suretly C

upvoted 1 times

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JoG1221

2 months, 3 weeks ago

Selected Answer: C

This approach is: Efficient: Only processes incremental data, not the full table Accurate: Ensures latest record per user_id Scalable: Works well with millions of users and hourly ingestion

upvoted 1 times

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Tedet

4 months, 2 weeks ago

Selected Answer: C

This option proposes filtering the records in the account_history table for the most recent records based on the last_updated field, which is exactly what you want to do to get the most recent value. The use of a MERGE statement ensures that only the most recent records are inserted or updated in the account_current table. This method avoids full overwrites of the account_current table and only updates records that have actually changed, which is efficient for large datasets. Conclusion: This is the most efficient approach because it ensures only the most recent data is merged, and it avoids unnecessary full table rebuilds.

upvoted 1 times

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Ananth4Sap

8 months, 3 weeks ago

C is correct because B is wrong as it says filtering the max value of last updated + overwriting we will miss some valid records. two valid scenarios: 1-Filtering the max value of last updated +merging (Option-c) 2.use window function on last update, filter and then overwrite (no options)

upvoted 3 times

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benni_ale

8 months, 3 weeks ago

Selected Answer: C

A. NO. Batch job required so AutoLoader and StructuredStreaming unecessarily complex solutions. B. NO. A full overwrite of the table is not efficient. C. YES. Seems it is filterning and merging on the id by using as less data as reasonable in the merge statement, why not? D. NO. Difference operation is very ineffecient for this purpose E. NO. Username is not key

upvoted 3 times

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Dhusanth

11 months, 1 week ago

Selected Answer: C

C is correct

upvoted 1 times

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faraaz132

11 months, 2 weeks ago

C is correct because: A record might have multiple changes and we need to select the most recent change that happened on that record. For that we will use max Log in date and rank it using window function, then we filter on rank=1 and use it for UPSERT operation.

upvoted 1 times

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Karunakaran_R

1 year, 1 month ago

I think B ,Type 1 table must overwrite the data

upvoted 1 times

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Freyr

1 year, 1 month ago

C is correct. A Type 1 table means that it performs an "upsert" operation without maintaining history, based on the merge condition. This means that new records are inserted, and existing records are updated. As a result, the merge process does not retain historical records. Therefore, the correct answer is C.

upvoted 3 times

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