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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Exploring Splunk's Search Processing Language | 15% | - Using search macros - Using tags and event types - Using transactions - Using workflow actions - Using advanced search commands |
| Topic 2: Exploring eval Command Functions | 4% | - Using conversion functions - Using makeresults command - Using informational functions - Using text functions - Using comparison and conditional functions - Using statistical functions |
| Topic 3: Exploring Alerts | 4% | - Logging and indexing searchable alert events - Referencing alert actions - Using alert manager - Understanding alert actions |
| Topic 4: Exploring Statistical Commands | 4% | - Using fieldsummary - Using eventstats - Using appendpipe - Performing statistical analysis with stats function - Using count and list functions - Using streamstats |
| Topic 5: Exploring Dashboards and Forms | 15% | - Using drilldowns - Creating dashboards using Simple XML - Using dynamic form inputs - Using event handlers - Using tokens |
| Topic 6: Exploring Data Models | 10% | - Understanding data models - Creating data models - Using pivot - Using data model objects |
| Topic 7: Exploring Lookups | 4% | - Understanding best practices for lookups - Using KV Store lookups - Using external lookups - Using geospatial lookups - Applying advanced lookup options - Including and excluding events based on lookup values |
| Topic 8: Exploring Search Optimization | 10% | - Using summary indexing - Using search optimization techniques - Using tsidx files - Using report acceleration |
| Topic 9: Exploring Field Extractions | 10% | - Creating custom fields - Using calculated fields - Using the Field Extractor - Using field aliases |
>> SPLK-1004 Exam Guide Materials <<
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NEW QUESTION # 14
What is the value of base lispy in the Search Job Inspector for the search index=sales clientip=170.192.178.10?
Answer: D
Explanation:
The base lispy expression represents how Splunk parses and simplifies a search command. In this case, the lispy format shows how Splunk is breaking down the search terms to effectively perform the search.
NEW QUESTION # 15
What order of incoming events must be supplied to the transaction command to ensure correct results?
Answer: C
Explanation:
The transaction command requires events in ascending chronological order to group related events correctly into meaningful transactions.
NEW QUESTION # 16
What is used to separate multiple tokens when creating a drilldown in XML?
Answer: C
Explanation:
Comprehensive and Detailed Step by Step Explanation:
InSplunk XML dashboards, multiple tokens must beseparated using an escaped ampersand (&), which prevents syntax errors and ensures that tokens are correctly passed in drilldowns.
Reference:Splunk Documentation - Token Usage
NEW QUESTION # 17
Which statement about the coalesce function is accurate?
Answer: A
Explanation:
The coalesce function in Splunk is used to evaluate each argument in order and return the first non-null value.
This function can be used within an eval expression to create a new field in the results set, which will contain the first non-null value from the list of fields provided as arguments to coalesce. This makes it particularly useful in situations where data may be missing or inconsistently populated across multiple fields, as it allows for a fallback mechanism to ensure that some value is always presented.
NEW QUESTION # 18
Repeating JSON data structures within one event will be extracted as what type of fields?
Answer: B
Explanation:
When Splunk encounters repeating JSON data structures in an event, they are extracted as multivalue fields. These allow multiple values to be stored under a single field, which is common with arrays in JSON data.
NEW QUESTION # 19
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