Question 1

You are connecting to a secure Hadoop dueler from Pentaho and want to use impersonation. Which Pentaho tool should you use?

Accepted Answer

B

Explanation: Pentaho Spoon, also known as Pentaho Data Integration (PDI), is the design tool used to create ETL (Extract, Transform, Load) jobs and transformations. When connecting to a data source like a secure Hadoop cluster, Spoon provides the graphical interface to configure the connection details. This includes setting up security parameters such as Kerberos authentication and enabling user impersonation, which allows a Pentaho job to run on the Hadoop cluster as a specific end-user.

Question 2

You are encryption your database connection password to use in the kettle. properties file. The output of the encr script is: Encrypted XYZabc123 In this scenario, which syntax is correct?

Accepted Answer

D

Explanation: The correct syntax for using an encrypted password in the kettle.properties file is VARIABLENAME=Encrypted . The Pentaho Data Integration (PDI) engine recognizes the Encrypted prefix and automatically decrypts the password string at runtime. The encr script generates this entire value string (Encrypted XYZabc123). Although option D contains typos (a hyphen - instead of an equals sign = and XY2 instead of XYZ), it is the only option that correctly reflects the required structure of the Encrypted keyword followed by a space and the encrypted value.

Question 3

you want to make a dynamic PDI transformation that is driven with variables that are loaded from a properties file. Which free form text fields within a step can be configured with variables?

Accepted Answer

NONE OF THE OPTIONS ARE CORRECT.

Explanation: In the Pentaho Data Integration (PDI) Spoon client, free-form text fields that support variable substitution are marked with a small icon, typically a green or grey diamond containing a dollar sign ($). This visual cue indicates that you can use the ${VARIABLENAME} or %%VARIABLENAME%% syntax. Additionally, pressing CTRL+SPACE within these fields usually displays a list of available variables for insertion. The symbols listed in the options (V, @, ') are not the standard indicators used in the PDI interface for this purpose.

Question 4

A Big Data customer wants to run POI transformations on Spark on their production Hadoop cluster
using Pentaho's Adaptive Execution Layer (AEL)
What are two steps for installing AEL? (Choose two.)
Choose 2 answers

Accepted Answer

A, D

Explanation: To install Pentaho's Adaptive Execution Layer (AEL) for use with Spark on a production Hadoop cluster, two key steps are required. First, the Spark application builder tool (spark-app-builder.sh) must be run. This utility packages the AEL daemon and all its dependencies into a single distributable zip file (ael-daemon-spark.zip). Second, the AEL daemon must be configured to run in YARN mode. This is accomplished by setting the ael.spark.master property to yarn in the config.properties file, which allows AEL to leverage the cluster's YARN resource manager for running Spark jobs, a standard practice for production Hadoop environments.

Question 5

You are running a PDI Job and you need to identify when something fails for a specific job entry to notify the sysops team about the failure. Which statement is correct in this scenario?

Accepted Answer

B

Explanation: In Pentaho Data Integration (PDI), job workflow is controlled by hops that connect job entries. To execute a specific action, such as sending a notification, only when a job entry fails, you must use the "On Failure" hop. This hop type is represented by a red arrow and is also referred to as the "false evaluation" hop. It ensures that the subsequent job entry (e.g., a "Mail" or "Write to Log" step) is triggered exclusively upon the failure of the preceding entry, which directly addresses the scenario's requirement for failure-specific notification.

Question 6

Which three file formats are splittable on HDFS? (Choose three). Choose 3 answers Choose 3 answers

Accepted Answer

A, C, E

Explanation: A file format is considered splittable in HDFS if a large file can be logically divided into chunks that can be processed independently and in parallel by different nodes. - Text files (.txt): These are splittable because data is typically separated by newlines. A processing framework like MapReduce can read a block of data, and if the split starts in the middle of a line, it can easily discard the first partial line and synchronize at the beginning of the next full line. - Parquet: This is a columnar storage format designed for parallel processing in the Hadoop ecosystem. It structures data into row groups, which are designed to be read independently, making the format inherently splittable. - Avro: This is a row-based format that includes synchronization markers between blocks of data. These markers allow a reader to seek to any point in a file, find the next marker, and begin reading, which makes Avro files splittable.

Question 7

In a PDI transformation you are retrieving data from a large lookup table using a Database Lookup
step from improve performance, you enable caching in the step and use the Load all data from table
option.
In this scenario, which three statement s are correct about the data flow of the ‘Database Lookup
step? (Choose three.)

Accepted Answer

B, C, E

Explanation: When the 'Database Lookup' step in Pentaho Data Integration (PDI) is configured to cache and "Load all data from table," it pre-loads the entire lookup table into memory before processing the first input row. This has three key implications for the data flow: 1. The entire dataset is stored in the Java Virtual Machine's (JVM) heap, meaning sufficient heap space must be allocated to prevent OutOfMemoryError exceptions (B). 2. Once cached, the comparisons between the input stream's keys and the cached keys are performed in memory. By default, these Java-based string comparisons are case-sensitive (C). 3. The step is designed to return a single set of values for each input row. If multiple rows in the lookup table match the input key, the step will use the data from only the first matching row it encounters in the cache (E).

Question 8

What are two ways to schedule a PDI job stored in the repository? (Choose two.) Choose 2 answers

Accepted Answer

B, C

Explanation: The two primary methods for scheduling Pentaho Data Integration (PDI) jobs using external, command-line tools are with an OS-native scheduler like cron. The most direct method is using the kitchen script, which is the designated command-line utility for executing PDI jobs. It can connect to the Pentaho repository to locate and run the specified job, and cron can be used to schedule its execution (C). An indirect, but technically valid, method involves the pan script. While pan is designed to execute transformations, a transformation can contain a "Job Executor" step. This allows a wrapper transformation to call a PDI job. Therefore, one can use cron to schedule the pan script to run this wrapper transformation, which in turn executes the job (B).

Question 9

You need to download files from a web site as part of a PDI job. Which job entry will accomplish this task?

Accepted Answer

A

Explanation: The HTTP job entry in Pentaho Data Integration (PDI) is specifically designed to interact with web servers using the HTTP or HTTPS protocol. It can be configured to perform a GET request to a specified URL, which is the standard method for retrieving or downloading files from a website. The entry allows you to define the target URL and specify a local file path where the downloaded content will be saved, directly fulfilling the requirement of the task.

Question 10

Which two statements are correct about the Repository Explorer? (Choose two.) Choose 2 answers

Accepted Answer

B, D

Explanation: The Repository Explorer in Pentaho Data Integration (PDI) is the primary interface for managing content stored within the Pentaho Repository. Its core purpose is to provide file management and version control functionalities. Users can perform standard organizational tasks such as moving, renaming, and deleting repository objects like jobs and transformations. Additionally, to support multi-user collaboration and prevent conflicting edits, the Repository Explorer allows users to manually lock and unlock these assets. Creating new jobs/transformations is done in the main design canvas, and managing JDBC drivers is a separate configuration task.

Question 11

You are migrating to a new version of the Pentaho server and you want to import your old repository. What are two methods to accomplish this task? (Choose two.) Choose 2 answers

Accepted Answer

B, C

Explanation: When migrating a Pentaho Server, two primary methods are available for transferring the repository content. The import-export command-line script is designed for bulk operations, allowing an administrator to export the entire repository from the old server and import it into the new one. This is ideal for complete server migrations. Alternatively, the Pentaho Data Integration client (Spoon) provides a graphical user interface (GUI) method. Using the Tools > Repository > Import Repository menu, a user can import content from a previously exported file (.zip) into the new, connected repository.

Question 12

Which PDI step or entry processes data within the Hadoop cluster?

Accepted Answer

C

Explanation: The Pentaho MapReduce job entry is the component designed to execute data processing logic directly within the Hadoop cluster. It orchestrates a MapReduce job by taking PDI transformations for the Mapper and optional Combiner/Reducer phases and submitting them to the Hadoop framework. Hadoop then distributes these tasks across its data nodes, processing the data in parallel where it resides. This "push-down" processing leverages the distributed computing power of the cluster, which is the core intent of the question. The other options involve data movement to or from the cluster, but the processing itself occurs on the PDI server.

Question 13

What must be the first PDI step in a child transformation ingesting records from Kafka?

Accepted Answer

A

Explanation: In a standard Pentaho Data Integration (PDI) design pattern involving parent and child transformations, the parent is responsible for a specific task, such as data ingestion. In this scenario, the parent transformation would contain the Kafka Consumer step to poll and retrieve batches of records from the Kafka topic. The parent then passes these records to the child transformation for processing. The standard mechanism for a child transformation to receive data from its parent is the Get rows from result step. Therefore, this must be the first step in the child transformation to accept the incoming data stream originating from Kafka via its parent.

Question 14

You are developing the PDI solution for a customer. The customer requires that a set of SQL statements are executed on each connection to the database. Which method will satisfy this requirement?

Accepted Answer

B

Explanation: In Pentaho Data Integration (PDI), the Database Connection window is used to define how to connect to a data source. This window has an "Advanced" tab that contains a specific text area labeled "SQL to execute on connect". Any SQL statements entered into this field are automatically executed by PDI every time a new connection to the database is established using this specific connection definition. This feature is designed precisely to handle requirements such as setting session-specific variables, temporary tables, or security contexts immediately upon connection, ensuring a consistent environment for all subsequent steps in a transformation or job.

Question 15

You are implementing a Pentaho server repository for a customer. The customer will be using the Pentaho Scheduler. Which repository supports this requirement?

Accepted Answer

B

Explanation: The Pentaho Scheduler is an integral feature of the Pentaho Server. This server-side component is designed to automate the execution of jobs and transformations. For the scheduler to access and manage these artifacts, they must be stored in the server's central repository, which is officially known as the Pentaho Repository. This repository, typically implemented with Apache Jackrabbit (a JCR), is the only one that fully integrates with all Pentaho Server features, including scheduling, security, versioning, and content management through the Pentaho User Console.

Free Hitachi Vantara HCE-5920 Actual Exam Questions