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NEW QUESTION: 1
What is the responsibility of an extreme Programming (XP) customer role?
A. Interacting closely with users and representing the XP team
B. Writing the stories and acceptance tests for each story
C. Planning and task allocation for the developer and tester
D. Testing the daily increments of the software developed
Answer: B

NEW QUESTION: 2
You issue the following query:
SQL> SELECT AVG(MAX(qty))
FROM ord_items
GROUP BY item_no
HAVING AVG(MAX(qty))>50;
Which statement is true regarding the outcome of this query?
A. It gives an error because the HAVING clause is not valid.
B. It gives an error because the GROUP BY expression is not valid.
C. It executes successfully but does not give the correct output.
D. It executes successfully and gives the correct output.
Answer: A
Explanation:
Explanation/Reference:
Explanation:
The general form of the SELECT statement is further enhanced by the addition of the HAVING clause and becomes:
SELECT column|expression|group_function(column|expression [alias]),...} FROM table
[WHERE condition(s)]
[GROUP BY {col(s)|expr}]
[HAVING group_condition(s)]
[ORDER BY {col(s)|expr|numeric_pos} [ASC|DESC] [NULLS FIRST|LAST]];
An important difference between the HAVING clause and the other SELECT statement clauses is that it may only be specified if a GROUP BY clause is present. This dependency is sensible since group-level rows must exist before they can be restricted. The HAVING clause can occur before the GROUP BY clause in the SELECT statement. However, it is more common to place the HAVING clause after the GROUP BY clause. All grouping is performed and group functions are executed prior to evaluating the HAVING clause.

NEW QUESTION: 3
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this scenario, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You plan to create an Azure Databricks workspace that has a tiered structure. The workspace will contain the following three workloads:
A workload for data engineers who will use Python and SQL
A workload for jobs that will run notebooks that use Python, Spark, Scala, and SQL A workload that data scientists will use to perform ad hoc analysis in Scala and R The enterprise architecture team at your company identifies the following standards for Databricks environments:
The data engineers must share a cluster.
The job cluster will be managed by using a request process whereby data scientists and data engineers provide packaged notebooks for deployment to the cluster.
All the data scientists must be assigned their own cluster that terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists.
You need to create the Databrick clusters for the workloads.
Solution: You create a High Concurrency cluster for each data scientist, a High Concurrency cluster for the data engineers, and a Standard cluster for the jobs.
Does this meet the goal?
A. Yes
B. No
Answer: B
Explanation:
Explanation
No need for a High Concurrency cluster for each data scientist.
Standard clusters are recommended for a single user. Standard can run workloads developed in any language:
Python, R, Scala, and SQL.
A high concurrency cluster is a managed cloud resource. The key benefits of high concurrency clusters are that they provide Apache Spark-native fine-grained sharing for maximum resource utilization and minimum query latencies.
References:
https://docs.azuredatabricks.net/clusters/configure.html