An important application has been migrated to a database on an X5 Database Machine.
You are examining high-load SQL statements from this application, in an attempt to determine which ones will benefit from the Exadata Smart Scan capability.
Which three access paths always generate ''cell single block physical read'' or ''cell multiblock physical read'' requests?
You plan to migrate a database supporting an OLTP workload to your new X5 Database Machine.
The current database instance supports a large number of short duration sessions and a very high volume of short transactions.
Which three X5 Database Machine features can improve performance for this type of workload?
A: To further accelerate OLTP workloads, the Exadata Smart Flash Cache also implements a special algorithm to reduce the latency of log write I/Os called Exadata Smart Flash Logging.
C: Use the Write-Back Flash Cache feature to leverage the Exadata Flash hardware and make Exadata Database Machine a faster system for Oracle Database Deployments.
D: Exadata X5-2 introduces Extreme Flash Storage Servers. Each Extreme Flash storage server contains eight 1.6 TB state-of-the-art PCI Flash drives. PCI flash delivers ultra-high performance by placing flash memory directly on the high speed PCI bus rather than behind slow disk controllers and directors.
References:
http://www.oracle.com/technetwork/database/exadata/exadata-x5-2-ds-2406241.pdf
http://www.oracle.com/technetwork/articles/database/exadata-write-back-flash-2179184.html
Your X6 Exadata Database Machine is running Oracle Database 12c, and has a large database with some very large tables supporting OLTP workloads.
High-volume insert applications and high-volume update workloads access the same tables.
You wish to compress these tables without causing unacceptable performance overheads to the OLTP workload.
Which three are true regarding this requirement?
A: Creating a Table with Advanced Row Compression
The following example enables advanced row compression on the table orders:
CREATE TABLE orders ... ROW STORE COMPRESS ADVANCED;
B: ARCHIVE LOW compression (Exadata only), recommended for Archival Data with Load Time as a critical factor
You plan to migrate a database supporting both DSS and OLTP workloads to your new X5 Database Machine.
The workloads contain many complex aggregating functions and expensive joins on large partitioned tables in the DSS workload and indexed access for OLTP workloads.
Which three benefits accrue as a result of this migration?
There are 6 different kinds of Table Data Compression methods:
You issued these commands to all Exadata Storage Servers in an X6 Exadata Database Machine using dcli:
alter iormplan objective = low_latency
alter iormplan active
There are no database or category plans defined.
You are encountering disk I/O performance problems at certain times, which vary by day and week.
DSS and Batch workloads perform well some of the time.
Further investigation shows that at times, the workloads are all OLTP I/Os, at other times all batch I/Os, and sometimes a bit of each.
You wish to have disk I/O managed so that performance will be optimized for all workloads.
Which statements would you issue to all Exadata Storage Servers to achieve this?
The supported IORM objectives are auto, low_latency, balanced, and high_throughput. The recommended objective option is auto which allows IORM to continuously monitor the workloads, and select the best mode based on the active workloads currently on the cells.
References:
http://docs.oracle.com/cd/E80920_01/SAGUG/exadata-storage-server-iorm.htm
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