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NEW QUESTION: 1
You are developing a SQL Server Analysis Services (SSAS) tabular project.
The model includes a table named Sales.
The Sales table includes a single date column.
The Sales table must meet the following requirements:
- Queries must be able to return all rows.
- Must be able to support four different processing schedules for
different date ranges.
- Date ranges must not include any overlapping data.
You need to implement a solution that meets the requirements.What should you do?
A. Create four partitions for the Sales table. Use row filter queries for each partition.
B. Convert the Sales table into four smaller tables by using row filter queries. Use one perspective for each of the four tables.
C. Convert the Sales table into four smaller tables by using row filter queries. Use one perspective for all four tables.
D. Create four partitions for the Sales table. Create four roles. Use the same row filter queries for each role and partition.
Answer: A
NEW QUESTION: 2
Your OnCommand Cloud Manager Instance has database corruption. You create a new OnCommand Cloud Manager instance with no data, and your ONTAP instances are still running with no issues. You want to bring the cloud and on-premlses ONTAP Instances into the new OnCommand Cloud Manager working environment.
In this scenario, which two actions will satisfy these requirements? (Choose two.)
A. Import ActivelQ entitlements.
B. Restore the 7z backup file.
C. Promote a load sharing mirror.
D. Discover the ONTAP instances.
Answer: C,D
NEW QUESTION: 3
列グループの使用状況を取得し、SHschemaの顧客テーブルのより良い基数予想の拡張統計情報を収集したいと思います。
次の手順を確認します:
1.デュアル声明からSELECTDBMS_STATS. CREATE_EXTENDED_STATS('SH','CUSTOMERS')を発行します。
2.dbms_stats.seed_col_usage (null,'SH',500)プロシージャを実行します。
3.顧客テーブルで必要なクエリーを実行します。
4.デュアル声明から選択dbms_stats.reportwcol_usage('SH', 'customers')を発行します。
正しい手順を識別してください。
A. 2, 3, 4, 1
B. 4, 1, 3, 2
C. 3, 2, 4, 1
D. 3, 2, 1, 4
Answer: A
Explanation:
Explanation
Step 1 (2). Seed column usage
Oracle must observe a representative workload, in order to determine the appropriate column groups. Using the new procedure DBMS_STATS.SEED_COL_USAGE, you tell Oracle how long it should observe the workload.
Step 2: (3) You don't need to execute all of the queries in your work during this window. You can simply run explain plan for some of your longer running queries to ensure column group information is recorded for these queries.
Step 3. (1) Create the column groups
At this point you can get Oracle to automatically create the column groups for each of the tables based on the usage information captured during the monitoring window. You simply have to call the DBMS_STATS.CREATE_EXTENDED_STATS function for each table.This function requires just two arguments, the schema name and the table name. From then on, statistics will be maintained for each column group whenever statistics are gathered on the table.
Note:
* DBMS_STATS.REPORT_COL_USAGE reports column usage information and records all the SQL operations the database has processed for a given object.
* The Oracle SQL optimizer has always been ignorant of the implied relationships between data columns within the same table. While the optimizer has traditionally analyzed the distribution of values within a column, he does not collect value-based relationships between columns.
* Creating extended statistics
Here are the steps to create extended statistics for related table columns withdbms_stats.created_extended_stats:
1 - The first step is to create column histograms for the related columns.
2 - Next, we run dbms_stats.create_extended_stats to relate the columns together.
Unlike a traditional procedure that is invoked via an execute ("exec") statement, Oracle extended statistics are created via a select statement.