To answer this question, you need to understand the internal scripting language of the DataStage Engine.

Option A) Shell Script - This option is incorrect because Shell Script is not the internal scripting language of the DataStage Engine. Shell Script is a scripting language commonly used for automating tasks in Unix-based operating systems.

Option B) OSH - This option is correct. OSH (Orchestrate Shell) is the internal scripting language of the DataStage Engine. It is used to define and control the execution of DataStage jobs and perform various data integration tasks.

Option C) Scriptella - This option is incorrect. Scriptella is an open-source ETL (Extract, Transform, Load) and script execution framework, but it is not the internal scripting language of the DataStage Engine.

Option D) All the above - This option is incorrect because only option B (OSH) is the correct internal scripting language of the DataStage Engine.

The correct answer is B) OSH. This option is correct because OSH is the internal scripting language specifically designed for the DataStage Engine.

• Thanks
• Wrong explanation

To answer this question, you need to understand different methods for resizing partitions of an input data set.

Option A) Range - This option is incorrect because the range method is used to divide a data set into partitions based on a specified range of values. It is not specifically designed for resizing partitions that are not equal in size.

Option B) Round Robin - This option is correct. The round robin method is a useful technique for resizing partitions of an input data set that are not equal in size. In this method, each partition is allocated an equal amount of data in a cyclic manner. This ensures that each partition receives a fair share of the data, even if the partitions have different sizes.

Option C) Hash - This option is incorrect. The hash method is used to allocate data to partitions based on a hash function. It is not specifically designed for resizing partitions that are not equal in size.

Option D) Same - This option is incorrect because the "Same" method implies that all partitions will have the same size. It is not suitable for resizing partitions that are not equal in size.

The correct answer is B) Round Robin. This option is correct because the round robin method is specifically designed for resizing partitions of an input data set that are not equal in size.

• Thanks
• Wrong explanation

To answer this question, we need to understand what impersonation mode is and which operating systems support it.

Impersonation mode is a feature that allows a program or process to temporarily adopt the security credentials of another user or account. This can be useful in certain scenarios, such as when a program needs to access resources that are restricted to specific users or accounts.

Based on this understanding, let's go through each option:

Option A) UNIX - UNIX operating systems do support impersonation mode. Therefore, this option is incorrect.

Option B) LINUX - Linux operating systems also support impersonation mode. Therefore, this option is incorrect.

Option C) WINDOWS - Windows operating systems do not support impersonation mode. Therefore, this option is correct.

Option D) ALL THE ABOVE - Since Windows does not support impersonation mode, option D is incorrect.

The correct answer is C) WINDOWS. This option is correct because Windows operating systems do not support impersonation mode.

• Thanks
• Wrong explanation

To answer this question, we need to understand the different execution modes in Datastage 8.5 and their implications.

A. Combinability mode - This mode allows the XML stage to combine the data from multiple partitions into a single output file. However, in Datastage 8.5, the XML stage does not support the combinability mode.

B. Parallel mode - This mode allows for parallel processing of data across multiple partitions. However, it does not address the requirement of creating a single XML document with data from multiple partitions.

C. Impersonation mode - This mode is not directly related to the requirement of creating a single XML document with data from multiple partitions.

D. Sequential mode - This mode processes the data sequentially, meaning it processes one partition at a time. In this mode, the XML stage can be used to create a single XML document with data from multiple partitions. Therefore, the correct answer is D.

The correct answer is D.

• Thanks
• Wrong explanation

To answer this question, we need to understand the concept of node configuration in Datastage 8.5.

Datastage is an ETL (Extract, Transform, and Load) tool used for data integration and data transformation tasks. It enables users to design and execute workflows, known as jobs, that extract data from multiple sources, transform it according to business rules, and load it into target systems.

In Datastage, a node represents a physical or virtual server where Datastage components can be installed and executed. Nodes are used to distribute the workload of a job across multiple servers, improving performance and scalability.

The maximum number of nodes that can be configured in Datastage 8.5 is 8 (Option C). This means that you can install and configure Datastage components on up to 8 servers to distribute the workload of a job.

Option A (10) and Option B (6) are incorrect because they do not represent the maximum number of nodes that can be configured in Datastage 8.5.

Option D (infinity) is incorrect because there is a limit to the number of nodes that can be configured in Datastage 8.5, which is 8.

Therefore, the correct answer is C.

• Thanks
• Wrong explanation

To answer this question, we need to understand how division by zero is handled in DataStage 8.5.

In DataStage 8.5, if division operation has to be performed in the Transformer stage, and the numerator is 1 while the denominator is 0, the output will be zero.

The correct answer is A) Zero.

This is because in DataStage 8.5, dividing any number by zero results in zero. It does not throw an error or abort the job.

• Thanks
• Wrong explanation