Oracle 1Z0-067 Questions Answers

Which two statements are true about scheduling operations in a pluggable database (PDB)?

A. Scheduler jobs for a PDB can be defined only at the container database (CDB) level.
B. A job defined in a PDB runs only if that PDB is open.
C. Scheduler attribute setting is performed only at the CDB level.
D. Scheduler objects created by users can be exported or imported using Data Pump.
E. Scheduler jobs for a PDB can be created only by common users.

Answer: BD


Which three statements are true about a job chain?

A. It can contain a nested chain of jobs.
B. It can be used to implement dependency-based scheduling.
C. It cannot invoke the same program or nested chain in multiple steps in the chain.
D. It cannot have more than one dependency.
E. It can be executed using event-based or time-based schedules.

Answer: ABE

https://education.oracle.com/upgrade-oracle9i-10g-11g-oca-to-oracle-database-12c-ocp/pexam_1Z0-067

https://www.dumpspedia.com/1z0-067-dumps-questions.html

Oracle 1Z0-067 Questions Answers

You plan to use the In-Database Archiving feature of Oracle Database 12c, and store rows that are inactive for over three months, in Hybrid Columnar Compressed (HCC) format.
Which three storage options support the use of HCC?

A. ASM disk groups with ASM disks consisting of Exadata Grid Disks.
B. ASM disk groups with ASM disks consisting of LUNS on any Storage Area Network array
C. ASM disk groups with ASM disks consisting of any zero padded NFS-mounted files
D. Database files stored in ZFS and accessed using conventional NFS mounts.
E. Database files stored in ZFS and accessed using the Oracle Direct NFS feature
F. Database files stored in any file system and accessed using the Oracle Direct NFS feature
G. ASM disk groups with ASM disks consisting of LUNs on Pillar Axiom Storage arrays

Answer: A,E,G

Oracle HPC Cloud Aims At Mainstream Business Data

ERP managers are finding more reasons to resort to high performance computing to improve the performance of big data analytics and machine learning models.

ERP systems have a huge amount of data that many companies are just beginning to use. To answer complex questions with this information, and to do it quickly, a lot of computing power is needed. It's one of the reasons why Oracle has just added a high-performance computing capability, or HPC, to the cloud to its portfolio of public cloud infrastructure services.

Oracle's new HPC cloud capability targets two audiences. The first is the users who run legacy HPC applications in their facilities, such as scientific projects, R & D applications and virtual product design instead of physical prototypes. The second audience is the ERP managers who need to apply high quality computing resources to the business data processed in the Oracle Cloud Infrastructure service.

ERP systems manage a large amount of data. "The majority of our customers today are trying to find more and more value from that data, and that is what we are seeing [as] growth," said Karan Batta, director of product management for Oracle Cloud Infrastructure.

HPC expands to the main commercial uses

The use of HPC outside of its scientific and traditional research use is expanding into areas such as sales analysis and planning, supply chain planning and workforce analysis related to human resources, said Steve Conway, Senior Vice President of Research at HPC Hyperion Research Research Firm in St. Paul, Minn.

An HPC system can absorb much more data to allow deeper analysis. This approach is also being combined with artificial intelligence technologies, such as an inference engine that can be applied to many situations in ERP, said Conway.

"The larger the data sets, the more accurate the results will be," he said.

Companies not only want questions related to ERP to be answered "that are more complicated than before, but they also want the answers in a time very close to the real," said Conway.

HPC ideal for machine learning models.

High performance computing is a set of technologies and processes designed to maximize performance. What Oracle HPC offers users is a clustered network with access to full processing, both CPU and GPU. Bare Metal is a single-tenant server or system that does not use virtualization, which can add latency.

Another key technology used by Oracle HPC to accelerate performance is remote remote access to memory (RDMA), which allows an application to write directly to memory remotely without involving the CPU or the operating system.

The use of bare metal and RDMA in a cloud platform means that providers are "overcoming one of the big bottlenecks that affected much of cloud computing, which is virtualization," said Conway.

Business application developers can take giant data sets from ERP systems and place this data in an automatic learning model. From that model, a company can find out what "type of information they can generate from that data" and then send it back to the ERP system, said Batta.

Batta said that machine learning models are computationally intensive and can take hours, days or even weeks to run if they do not have access to enough computing resources. That's where high-performance computing comes in.

Oracle's HPC system will scale up to 1,080 cores for a single project, although the number of cores available will be extended over time, Batta said.

Oracle 1Z0-067 Question Answer

In your database, the tbs percent used parameter is set to 60 and the tbs percent free parameter is set to 20. Which two storage-tiering actions might be automated when using Information Lifecycle Management (ILM) to automate data movement?

A. The movement of all segments to a target tablespace with a higher degree of compression, on a different storage tier, when the source tablespace exceeds tbs percent used
B. Setting the target tablespace to read-only after the segments are moved
C. The movement of some segments to a target tablespace with a higher degree of
compression, on a different storage tier, when the source tablespace exceeds T3Spercent used
D. Taking the target tablespace offline after the segments are moved
E. The movement of some blocks to a target tablespace with a lower degree of compression, on a different storage tier, when the source tablespace exceeds tbs percent used

Answer: B,C


Which two statements are true abouta multitenant architecture?

A. Each pluggable database (PDB) has its own initialization parameter file.
B. A PDB can have a private undo tablespace.
C. Log switches occur only at the container database level.
D. A PDB can have a private temporary tablespace.
E. Each PDB has a private control file.

Answer: C,D

Oracle 1Z0-067 Question Answer

View the SPFILE parameter settings in the Exhibit.

You issue this command and get errors:
SQL> startup
ORA-00824:cannotsetSGAJTARGET or MEMORY_TARGET dueto existing
internalsettings,seealertlog for moreinformation Why did the instance fail to start?

A. because pga_aggregate_target is not set
B. because statistics_level is set to basic
C. because memory_target and memory_max_target cannot be equal
D. because sga_target and memory_target are both set

Answer: B

Deploying a Python App to Oracle ACCS

Let's take a look at how to deploy a Python app to Oracle's Application Container Cloud Service by way of an example!

ACCS provides a pre-configured platform (Platform as a Service) where you can quickly deploy and host your applications. For many of today’s applications, the hosting server is just that, a place to host the application. Most of the time the only thing an application needs from the server is to have it support the application’s programming language and to provide in and out connections through ports. Using a PAAS such as ACCS frees you from all of the extra work of configuring and maintaining a server and allows you to focus on perfecting your application.

ACCS supports multiple languages but for this post, I’ll focus on Python.

 DinoDate

For the examples, I will be deploying the DinoDate application. DinoDate was written as an open source learning application that can be used to demonstrate database concepts with multiple programming languages. It currently has both Python and NodeJS mid-tier applications and is backed by an Oracle Database.

The following instructions show how to deploy the Python version of DinoDate to an Oracle ACCS instance.

If you don’t have access to Oracle Cloud services, you can try the Oracle Cloud with $300 of free credit.

Database

First, you’ll need a database.

Create an Oracle Cloud database or if you already have an Oracle Database, make sure that you can safely create and destroy the DD and DD_NON_EBR schema.

Connect to your database as sys with sysdba and run coreDatabase/dd_master_install.sql. (Use your password and connect string)

sql sys/YourPassword@YourJdbcConnecString as sysdba @coreDatabase/dd_master_install.sql

Prepare the DinoDate Application

Download oraclejet.zip (version 4.1.0). (Current versions as of the time of this post.)

    Extract the Oracle JET files
    Run bower install

unzip oraclejet.zip -d dino-date/commonClient/jet/ cd dino-date/commonClient/jet/ bower install cd ../../


Download Necessary Files

The Docker container for Python used by ACCS comes with Python installed. We’ll need to include the rest of the dependencies.

    Oracle Instant Client Packages
        Basic Light
        JDBC Supplement
    Debian libaio package libaio1_0.3.110-1_amd64.deb

Package the Files to Deploy

•     Create a deploy directory with a lib subdirectory.
•     Copy the front end client into the deploy directory.
•     Copy the python application into the deploy directory.
•     Extract the Oracle instant client files into the deploy/lib directory. (Change the command to point to where your files are located.)

•     Change to the deploy directory.

mkdir -p deploy/lib cp -r commonClient/ deploy/ cp -r python/ deploy/ unzip instantclient-basiclite-linux.x64-12.2.0.1.0.zip -d deploy/lib unzip instantclient-sdk-linux.x64-12.2.0.1.0.zip -d deploy/lib cd deploy


Create a shell script, launchPython.sh, to install the dependencies and launch the application.

#!/bin/sh # Install the LIBAOI libs dpkg-deb -R libaio1_0.3.110-1_amd64.deb ${APP_HOME} # Install Python packages into python/modules folder pip --no-cache-dir install -r python/requirements.txt -t ${PYTHONPATH} #launch DinoDate cd python python app.py


Create the manifest file: manifest.json

This file declares that we will use Python version 3.6.0 and provides the command that will be used to start the application.

{ "runtime": { "majorVersion": "3.6.0" }, "command": "sh ./launchPython.sh", "release": {}, "notes": "DinoDate" }


Create the deployment file: deployment.json

This file includes the environment variables DinoDate needs and sets the ACCS deployment to use 1G of memory and only install 1 instance. PYTHONPATH is the directory we will install the Python modules into and LD_LIBRARY_PATH is used by cx_Oracle to locate the Oracle client files.

Replace “YourJdbcConnecString” with the JDBC connect string for your database.

{ "memory": "1G", "instances": "1", "environment": { "dd_connectString":"YourJdbcConnecString", "dd_user":"dd", "dd_password":"dd", "dd_clientAppCodeDir":"jet", "dd_python_clientAppCodeDir":"jet", "dd_python_port":"${PORT}", "PYTHONPATH":"${APP_HOME}/python/modules", "LD_LIBRARY_PATH":"${APP_HOME}/lib/instantclient_12_2:${APP_HOME}/lib/x86_64-linux-gnu" } }


Important Note

ACCS is pre-configured to listen on $PORT so we set our application to listen on that port. Do not attempt to change $PORT. When ACCS performs its post-deploy check it will open the application using $PORT, if the application is not listening on that port and returns a 404 the deployment will fail and be removed.

Create a zip file with the required DinoDate deploy files.

zip -rq DinoDatePythonACCS.zip commonClient/ python/ lib/ libaio1_0.3.110-1_amd64.deb launchPython.sh


Deploy to ACCS

In your browser navigate to the Oracle Application Container Cloud Service Console.

Push the Create Application button to open the platform selection panel.

Push the Python button to open the application definition panel and expand the ‘More Options’ section.

    Populate [Name] with DinoDatePython.

•     Click ‘Choose File’ for Archive and select the DinoDatePythonACCS.zip file.
•     Click ‘Choose File’ for Manifest and select the manifest.json file.
•     Click ‘Choose File’ for Deployment Configuration and select the deployment.json file.

You can change the values in the other fields as you’d like, but notice that since we defined “memory”: “1G” and “instances”: “1” in the deployment.json file those values will change automatically.

It’s also possible to include the manifest.json file in the DinoDatePythonACCS.zip file instead of uploading it separately.

Click Create.

It may take several minutes for ACCS to setup the environment and deploy the application. Once it’s done click on the URL: link to open the application.

Try It out

You can log in with any of the existing users, such as:

    Bobbob@example.com
    Adminadmin@example.com

Use any value for the password, the application doesn’t check it.

Click on the Search tab and search for ‘eat’ it should return 6 of the pre-loaded dinosaurs.

Quick Review

    Download the dependencies.
    Create a launch script that will install the dependencies and launch the application.
    Collect the required deployment artifacts and dependencies into a .zip file.
    Create a manifest.json file that contains at least the required Python version and the command used to start your application.
    Create a deployment.json file that contains any needed environment variable definitions. Optionally you can include ACCS environment definitions such as required memory and number of instances. (This file is optional. You could include the environment variables in your launch script.)Reminder: ACCS will use the pre-defined environment variable $PORT. Make sure your application listens on $PORT.

    Use the ACCS service console to upload your 3 files and create your new application.

If you run into any trouble, leave a comment and I’ll be happy to help.

Oracle 1Z0-067 Question Answer

Your database supports a Decision Support System (DSS)workload that involves the
execution of complex queries. Currently, the database is running with peak workload. You
want to analyze some of the most resource-intensive statements cached in the library
cache.
What must you run to receive recommendations on the efficient use of indexes and
materialized views to improve query performance?

A. SQL Performance Analyzer
B. SQL Access Advisor
C. SQL Tuning Advisor
D. Automatic Workload Repository (AWR) report
E. Automatic Database Diagnostic Monitor (ADDM)

Answer: B