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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

1. You launched a new gaming app almost three years ago. You have been uploading log files from the previous day to a separate Google BigQuery table with the table name format LOGS_yyyymmdd. You have been using table wildcard functions to generate daily and monthly reports for all time ranges. Recently, you discovered that some queries that cover long date ranges are exceeding the limit of 1,000 tables and failing. How can you resolve this issue?

A) Create separate views to cover each month, and query from these views
B) Convert all daily log tables into date-partitioned tables
C) Convert the sharded tables into a single partitioned table
D) Enable query caching so you can cache data from previous months

2. MJTelco needs you to create a schema in Google Bigtable that will allow for the historical analysis of the last 2 years of records. Each record that comes in is sent every 15 minutes, and contains a unique identifier of the device and a data record. The most common query is for all the data for a given device for a given day. Which schema should you use?

A) Rowkey: date#data_pointColumn data: device_id
B) Rowkey: device_idColumn data: date, data_point
C) Rowkey: data_pointColumn data: device_id, date
D) Rowkey: dateColumn data: device_id, data_point
E) Rowkey: date#device_idColumn data: data_point

3. Which is not a valid reason for poor Cloud Bigtable performance?

A) The workload isn't appropriate for Cloud Bigtable.
B) The Cloud Bigtable cluster has too many nodes.
C) The table's schema is not designed correctly.
D) There are issues with the network connection.

4. When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a proxy.

A) VPN
B) SOCKS
C) HTTP
D) HTTPS

5. You are responsible for writing your company's ETL pipelines to run on an Apache Hadoop cluster. The pipeline will require some checkpointing and splitting pipelines. Which method should you use to write the pipelines?

A) PigLatin using Pig
B) HiveQL using Hive
C) Python using MapReduce
D) Java using MapReduce

Solutions: