SPLK-1001 Practice Test 7 — 10 Questions

Question 1

A user runs a search that returns thousands of results. They need to see only the first 100 events after sorting by time descending. Which command should they use?

Accepted Answer

sort - _time | head 100. The user needs the first 100 events after sorting by time descending. The `sort - _time` command sorts events in descending order by timestamp, and piping the result to `head 100` returns the first 100 events from that sorted list, which are the most recent 100 events. This is the correct approach because `head` returns events from the top of the result set, and sorting ensures the top events are the newest.

Answer

reverse

Answer

tail 100

Answer

head 100

Question 2

Which THREE of the following are transforming commands in Splunk?

Accepted Answer

stats. The `stats`, `timechart`, and `chart` commands are all transforming commands in Splunk because they convert raw event data into statistical results, typically producing a table or time-based chart. Unlike non-transforming commands (e.g., `search` or `eval`), these commands change the data structure from events to a summary, which is required for visualizations and further statistical processing.

Answer

search

Answer

eval

Question 3

A user wants to remove duplicate events based on the 'transaction_id' field, keeping only the first occurrence. Which command is appropriate?

Accepted Answer

dedup transaction_id. The `dedup` command removes duplicate events based on specified fields, keeping only the first occurrence by default. Since the user wants to keep the first occurrence of each unique `transaction_id`, `dedup transaction_id` is the correct and simplest approach.

Answer

fields - transaction_id

Answer

sort transaction_id | dedup transaction_id

Answer

uniq transaction_id

Question 4

When tagging events in Splunk to map them to a data model, which tag is used to associate events with a specific data model dataset?

Accepted Answer

tag::=. In Splunk, the tag syntax `tag::=` is used to map events to a specific dataset within a data model. The tag key is the data model name, and the tag value is the dataset name, which allows Splunk's data model acceleration to correctly categorize events for reporting and pivot use.

Answer

tag::datamodel=<dataset>

Answer

tag::<datamodel>=<value>

Answer

tag::<dataset>=<datamodel>

Question 5

An organization wants to define a data model that represents transaction-level data from multiple source types, including web logs and application logs. They need to ensure that the data model is scalable and easy to maintain. Which best practice should the admin follow when designing this data model?

Accepted Answer

Use child objects under a root event to represent different sourcetypes, and assign appropriate constraints.. Using child objects under a root event allows the admin to model transaction-level data from multiple sourcetypes (e.g., web logs, application logs) within a single data model, promoting scalability and maintainability. By assigning appropriate constraints to each child object, the admin ensures that only relevant events are included, while the root event provides a common structure for transaction analysis. This approach follows Splunk best practices for data model design, enabling efficient searches and reducing duplication.

Answer

Create separate data models for each sourcetype to avoid complexity.

Answer

Avoid using constraints to ensure all events are included in the data model.

Answer

Include all possible fields that might ever be needed in the data model to avoid future modifications.

Question 6

A large e-commerce company ingests 10 TB/day of web access logs into Splunk. They have enabled the CIM-compliant Web data model and created data model acceleration with a 90-day range. Users run reports using pivot to analyze HTTP status codes, client IPs, and URIs. Recently, two issues arose: (1) Pivot reports are returning incomplete or outdated results, sometimes missing data from the last few hours. (2) Acceleration summary size has ballooned to over 500 GB, causing search head performance degradation. The Splunk admin suspects that data model acceleration is not configured optimally. Upon inspection, the Web data model's root search contains a complex filter with multiple eval commands and lookups, and the acceleration time range is set to the same 90 days as the summary range. The admin also notices that the data model is defined as non-time-based, even though the events have timestamps and the pivot often uses time ranges. What is the best course of action to resolve both issues while maintaining accuracy and performance?

Accepted Answer

Change the data model to time-based, narrow acceleration range to 7 days, and simplify the root search by removing expensive eval/ lookups and using search-time field extractions instead.. Making the data model time-based allows acceleration to use time-bucketed summaries, which ensures recent data is included in pivot results and prevents incomplete results. Narrowing the acceleration range to 7 days reduces the summary size drastically (from 500+ GB to a manageable size), and simplifying the root search by removing expensive eval/lookups improves acceleration build performance and reduces overhead. This directly addresses both issues: incomplete recent data and excessive summary size.

Answer

Change the data model to time-based and set acceleration to 180 days to cover all data.

Answer

Keep the data model as non-time-based but reduce acceleration range to 30 days and add a constraint to filter out irrelevant events.

Answer

Disable acceleration for the Web data model and instead create an accelerated search report for each common pivot query.

Question 7

A team is designing a data model for IT operations. They have fields like `src_ip`, `dest_ip`, `user`, and `action`. Which best practice should they follow when naming the root event dataset?

Accepted Answer

Use camelCase, e.g., 'itOperations'.. Splunk data model root event dataset names must follow camelCase naming conventions to ensure compatibility with the Splunk search language and to avoid parsing issues. CamelCase prevents spaces and special characters that could break field references in searches and data model acceleration.

Answer

Use underscores and numbers for clarity.

Answer

Use a short abbreviation like 'ITOps'.

Answer

Use a generic name like 'events'.

Question 8

A user wants to rename the field 'src_ip' to 'sourceIP' in all search results without modifying the raw data. Which method should they use?

Accepted Answer

Use the rename command: | rename src_ip as sourceIP. The `rename` command is the correct choice because it changes the field name in the search results without altering the underlying raw data. It operates on the field metadata in the search pipeline, allowing you to display 'sourceIP' instead of 'src_ip' for the duration of the search.

Answer

Use the eval command to assign src_ip to a new field sourceIP

Answer

Add an alias in props.conf

Answer

Use the fields command: | fields src_ip as sourceIP

Question 9

A user runs a search and uses `| lookup mylookup myfield OUTPUT myfield2`. The search returns events that have myfield values, but myfield2 is null. The lookup file has matching entries. What is the most likely issue?

Accepted Answer

The lookup definition is case-sensitive and the event values have different case.. The lookup definition in Splunk has a case-sensitivity setting. By default, lookups are case-insensitive, but if the lookup definition is configured to be case-sensitive, then the lookup will only match when the case of the event field value exactly matches the case in the lookup file. Since the events have myfield values but myfield2 is null, the lookup is failing to match due to case differences, even though the lookup file has matching entries.

Answer

The lookup definition is missing the max_matches setting.

Answer

The lookup file has duplicate keys.

Answer

The lookup command should use OUTPUTNEW instead of OUTPUT.

Question 10

A user has a lookup file containing employee email addresses and department names. They want to add the department field to search results containing the employee's email. Which command should they use?

Accepted Answer

lookup employee_department.csv email OUTPUT department. The `lookup` command is designed to enrich search results by matching a field in the events (e.g., email) against a lookup table (e.g., employee_department.csv) and outputting additional fields (e.g., department). Option B correctly uses the syntax `lookup employee_department.csv email OUTPUT department`, which performs a field-based lookup and appends the department field to matching events.

Answer

inputlookup employee_department.csv

Answer

eval department=employee_department(email)

Answer

outputlookup employee_department.csv