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NEW QUESTION: 1
DRAG DROP
Note: This question is part of a series of questions that present the same Scenario.
Each question I 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 correct solution.
Start of Repeated Scenario:
You are planning a big data infrastructure by using an Apache Spark Cluster in Azure
HDInsight. The cluster has 24 processor cores and 512 GB of memory.
The Architecture of the infrastructure is shown in the exhibit:
The architecture will be used by the following users:
* Support analysts who run applications that will use REST to submit Spark jobs.
* Business analysts who use JDBC and ODBC client applications from a real-time view.
The business analysts run monitoring quires to access aggregate result for 15 minutes.
The result will be referenced by subsequent quires.
* Data analysts who publish notebooks drawn from batch layer, serving layer and speed layer queries. All of the notebooks must support native interpreters for data sources that are bath processed. The serving layer queries are written in Apache Hive and must support multiple sessions. Unique GUIDs are used across the data sources, which allow the data analysts to use Spark SQL.
The data sources in the batch layer share a common storage container. The Following data sources are used:
* Hive for sales data
* Apache HBase for operations data
* HBase for logistics data by suing a single region server.
End of Repeated scenario.
The business analysts require to monitor the sales data. The queries must be faster and more interactive than the batch layer queries.
You need to create a new infrastructure to support the queries. The solution must ensure that you can tune the cache policies of the queries.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to answer area.
Answer:
Explanation:
NEW QUESTION: 2
Azure Resource Managerテンプレートを使用して、20のAzure仮想マシンをデプロイする予定です。仮想マシンは、Azure Marketplaceイメージを使用して、Windows Server 2016 Datacenterの最新バージョンを実行します。
テンプレートのstorageProfileセクションを完了する必要があります。
storageProfileセクションをどのように完了する必要がありますか？回答するには、回答領域で適切なオプションを選択します。
注：それぞれの正しい選択は1ポイントの価値があります。
Answer:
Explanation:
Explanation:
...
"storageProfile": {
"imageReference": {
"publisher": "MicrosoftWindowsServer",
"offer": "WindowsServer",
"sku": "2016-Datacenter",
"version": "latest"
},
...
References:
https://docs.microsoft.com/en-us/rest/api/compute/virtualmachines/createorupdate
NEW QUESTION: 3
You have a database that includes the following tables:
You need to create a list of all customer IDs and the date of the last order that each customer placed. If the customer has not placed any orders, you must return the date January 1, 1900. The column names must be CustomerID and LastOrderDate.
Which four Transact-SQL segments should you use to develop the solution? To answer, move the appropriate Transact-SQL segments from the list of Transact-SQL segments to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation
Box 1: SELECT..COALESCE...
The COALESCE function evaluates the arguments in order and returns the current value of the first expression that initially does not evaluate to NULL.
Box 2: ..LEFT OUTER JOIN..
The LEFT JOIN (LEFT OUTER JOIN) keyword returns all rows from the left table (table1), with the matching rows in the right table (table2). The result is NULL in the right side when there is no match. A customer might have no orders so the right table must be allowed have a NULL value.
Box 3: ON c.custid = o.custid
We JOIN on the custID column, which is available in both tables.
Box 4: GROUP BY c.custid
References:
https://technet.microsoft.com/en-us/library/ms189499(v=sql.110).aspx
http://www.w3schools.com/sql/sql_join_left.asp
NEW QUESTION: 4
You need to recommend the appropriate storage and processing solution?
What should you recommend?
A. Configure the reading speed using Azure Data Studio.
B. Enable Apache Spark RDD (RDD) caching.
C. Flush the blob cache using Windows PowerShell.
D. Enable Databricks IO (DBIO) caching.
E. Enable auto-shrink on the database.
Answer: B
Explanation:
Explanation
Scenario: You must be able to use a file system view of data stored in a blob. You must build an architecture that will allow Contoso to use the DB FS filesystem layer over a blob store.
Databricks File System (DBFS) is a distributed file system installed on Azure Databricks clusters. Files in DBFS persist to Azure Blob storage, so you won't lose data even after you terminate a cluster.
The Databricks Delta cache, previously named Databricks IO (DBIO) caching, accelerates data reads by creating copies of remote files in nodes' local storage using a fast intermediate data format. The data is cached automatically whenever a file has to be fetched from a remote location. Successive reads of the same data are then performed locally, which results in significantly improved reading speed.
References:
https://docs.databricks.com/delta/delta-cache.html#delta-cache