SPLK-1002 Exam Dumps

Explanation

This search uses the transaction command to group events that share a common value for JSESSIONID into transactions1.

The transaction command assigns a duration field to each transaction, which is the difference between the latest and earliest timestamps of the events in the transaction1. The search then uses the timechart command to create a time-series chart of the average duration of each transaction1.

Therefore, option A is correct because it describes the search accurately.

Option B is incorrect because the search does not use the stats command or the pause field.

Option C is incorrect because the transaction command does not require the startswith and endswith options, although they can be used to specify how to identify the beginning and end of a transaction1.

Option D is incorrect because the transaction command does not have to be the last command in the search pipeline, although it is often used near the end of a search1.

Explanation:

Delimiter-based field extraction in Splunk is designed to parse structured text files where fields are separated by a specific character (e.g., commas, tabs, pipes).

Why CSV?
CSV (Comma-Separated Values) files use a delimiter (typically ,) to separate fields, making them ideal for this extraction method.

Example:
csv
timestamp,user,action
2023-10-01,admin,login
Splunk can split this into timestamp, user, and action fields using comma-delimited extraction.

Why Not the Others?
B) PDF → Unstructured/binary data; requires OCR or specialized extraction.
C) XML → Hierarchical format; use spath or XML-specific extractions.
D) JSON → Nested structure; use spath or automatic JSON extraction.

Key Takeaway:
✔ Use delimiter extraction for:
CSV, TSV, pipe-delimited (|), or other uniformly separated data.
✔ For JSON/XML, use:
Automatic parsing (JSON) or spath (XML/JSON).

Explanation:

In Splunk, when multiple event types are matched to the same event, each event type may have its own color and priority value. To determine which color is displayed, Splunk uses the priority assigned to the event type.

✅ Priority in Event Types:
Priority is an integer value from 1 (highest) to 10 (lowest).
The event type with the highest priority (lowest number) determines the color shown for the event in the search results.

Example:
If an event matches:
Event type A (priority 5, color red)
Event type B (priority 2, color blue)
➡️ The event will be displayed with the color blue (because event type B has a higher priority).

❌ Why the other options are incorrect:
A. Rank – Not a Splunk concept in this context.
B. Weight – Not applicable for event types.
D. Precedence – Not used for determining color; Splunk uses the term "priority."

Explanation:

The search:
spl
index=corndogs type=mysterymeat action=eaten | stats count by user

Does the following:
Filters events where:
index=corndogs
type=mysterymeat (only "mysterymeat" corndogs)
action=eaten (only eaten actions)
Aggregates results with stats count by user:
Counts how many times each user ate "mysterymeat" corndogs.

Why Not the Other Options?
A) Incorrect—counts are split by user, not corndog type.
C) Incorrect—only counts "mysterymeat" type (not all types).
D) Incorrect—no filter for "vegetarian" exists in the search.

Key Takeaway:
✔ stats count by field creates a table of counts grouped by the specified field.
✔ Filtering (type=mysterymeat) restricts the analysis to a subset of data.

Explanation: Data model acceleration is a feature that speeds up searches on data models by creating and storing summaries of the data model datasets1. To enable data model acceleration, you must have administrative permissions or the accelerate_datamodel capability1. Therefore, option D is correct. Accelerated data models cannot be edited unless you disable the acceleration first1. Therefore, option B is correct. Private data models cannot be accelerated because they are not visible to other users1. Therefore, option C is correct. Root events can be accelerated as long as they are not based on a search string1. Therefore, option A is incorrect.

A pivot is a tool that allows you to create reports and dashboards using data models without writing any SPL commands2. You can use pivots to explore, filter, split and visualize your data using a graphical interface2. Pivots are designed for users who want to analyze and report on their data without having to learn the SPL syntax or the underlying structure of the data2. Therefore, option A is correct, while options B, C and D are incorrect because they are not the typical group of users who would use pivots.

Explanation: After manually editing a regular expression (regex) that was created using the Field Extractor (FX) UI, it is no longer possible to edit the field extraction in the FX UI. The FX UI is a tool that helps you extract fields from your data using delimiters or regular expressions. The FX UI can generate a regex for you based on your selection of sample values or you can enter your own regex in the FX UI. However, if you edit the regex manually in the props.conf file, the FX UI will not be able to recognize the changes and will not let you edit the field extraction in the FX UI anymore. You will have to use the props.conf file to make any further changes to the field extraction. Changes made manually cannot be reverted in the FX UI, as the FX UI does not keep track of the changes made in the props.conf file. It is possible to manually edit a regex that was created using the FX UI, as long as you do it in the props.conf file.

Explanation: The Splunk Common Information Model (CIM) add-on helps you normalize your data from different sources and make it easier to analyze and report on it3. One of the functionalities that the CIM add-on relies on to normalize fields with different names is field aliases3. Field aliases allow you to assign an alternative name to an existing field without changing the original field name or value2. By using field aliases, you can map different field names from different sources or sourcetypes to a common field name that conforms to the CIM standard3. Therefore, option B is correct, while options A, C and D are incorrect.

The fillnull command is a search command that replaces null values with a specified value or 0 if no value is specified. Null values are values that are missing, empty, or undefined in Splunk. The fillnull command can replace null values for all fields or for specific fields. The fillnull command can take an optional argument called value that specifies the value to replace null values with. If no value argument is specified, the fillnull command will replace null values with 0 by default.

An event type is a way to categorize events based on a search string that matches the events2. You can use event types to simplify your searches by replacing long or complex search strings with short and simple event type names2. An event type is more effective than a saved search when the search string needs to be used in future searches because it allows you to reuse the search string without having to remember or type it again2. Therefore, option C is correct, while options A, B and D are incorrect because they are not scenarios where an event type is more effective than a saved search.