Get Splunk SPLK-2002 Exam Practice Questions - Real and Updated

Answer : A, B, C

A deployment plan should include business continuity and disaster recovery plans, current logging details and data source inventory, and current and future topology diagrams of the IT environment. These elements are essential for planning, designing, and implementing a Splunk deployment that meets the business and technical requirements. A comprehensive list of stakeholders, either direct or indirect, is not part of the deployment plan, but rather part of the project charter. For more information, seeDeployment planningin the Splunk documentation.

Answer : C

The walklex command in Splunk is a specialized administrative search command used to translate and display LISPY (Splunk's internal representation of search terms). LISPY is the logical search syntax Splunk uses to parse and execute search queries, and examining it helps administrators and developers debug search optimization, field extraction behavior, and index-time search efficiency.

When you run the command | walklex search='your_search_string', Splunk outputs how it tokenizes and interprets that query internally. This is particularly useful for understanding how Splunk's search language maps to index-time fields and for diagnosing performance issues caused by inefficient search term parsing.

For example:

| walklex search='error OR failure host=server01'

Displays the corresponding LISPY translation used by Splunk's search subsystem.

Other options are unrelated:

dbinspect provides index bucket metadata.

Monitoring Console shows performance metrics and health status.

Search Job Inspector analyzes search execution phases but doesn't expose LISPY.

Thus, the correct and Splunk-documented tool for LISPY inspection is the walklex command.

Reference (Splunk Enterprise Documentation):

* walklex Command Reference -- LISPY and Search Debugging

* Understanding Search Language Parsing in Splunk

* Search Internals: How Splunk Interprets Queries

* Splunk Search Performance Troubleshooting Tools

Answer : D

To reduce the captain's work load in a search head cluster, the setting that will prevent scheduled searches from running on the captain is captain_is_adhoc_searchhead = true (on the current captain). This setting will designate the current captain as an ad hoc search head, which means that it will not run any scheduled searches, but only ad hoc searches initiated by users. This will reduce the captain's work load and improve the search head cluster performance. The adhoc_searchhead = true (on all members) setting will designate all search head cluster members as ad hoc search heads, which means that none of them will run any scheduled searches, which is not desirable. The adhoc_searchhead = true (on the current captain) setting will have no effect, as this setting is ignored by the captain. The captain_is_adhoc_searchhead = true (on all members) setting will have no effect, as this setting is only applied to the current captain. For more information, seeConfigure the captain as an ad hoc search headin the Splunk documentation.

Answer : D

According to the Splunk documentation1, one of the benefits of search head clustering is the automatic replication of user knowledge objects, such as dashboards, reports, alerts, and tags. This ensures that all cluster members have the same set of knowledge objects and can serve the same search results to the users. The other options are false because:

Allowing indexers to maintain multiple searchable copies of all data is a benefit of indexer clustering, not search head clustering2.

Input settings are not synchronized between search heads, as search head clusters do not collect data from inputs.Data collection is done by forwarders or independent search heads3.

Fewer network ports are not required to be opened between search heads, as search head clusters use several ports for communication and replication among the members4.

Answer : C, D

According to the Splunk documentation1, a bucket within a clustered index contains two key types of files: the raw data in compressed form (rawdata) and the indexes that point to the raw data (tsidx files). A bucket can be either replicated or searchable, depending on whether it has both types of files or only the rawdata file. A replicated bucket is a bucket that has been copied from one peer node to another for the purpose of data replication. A searchable bucket is a bucket that has both the rawdata and the tsidx files, and can be searched by the search heads. The types of files that exist in a bucket within a clustered index are:

Inside a searchable bucket, there is tsidx and rawdata.This is true because a searchable bucket contains both the data and the index files, and can be searched by the search heads1.

Inside a replicated bucket, there is both tsidx and rawdata. This is true because a replicated bucket can also be a searchable bucket, if it has both the data and the index files.However, not all replicated buckets are searchable, as some of them might only have the rawdata file, depending on the replication factor and the search factor settings1.

The other options are false because:

Inside a replicated bucket, there is only rawdata. This is false because a replicated bucket can also have the tsidx file, if it is a searchable bucket.A replicated bucket only has the rawdata file if it is a non-searchable bucket, which means that it cannot be searched by the search heads until it gets the tsidx file from another peer node1.

Inside a searchable bucket, there is only tsidx. This is false because a searchable bucket always has both the tsidx and the rawdata files, as they are both required for searching the data.A searchable bucket cannot exist without the rawdata file, as it contains the actual data that the tsidx file points to1.