SPLK-1002 Advanced Visualization and Lookups Practice Test 8 — 15 Questions

Question 1

Refer to the exhibit. A user runs this search expecting to see the top 5 departments by count, but the results show all departments. What is the error?

Accepted Answer

The top command already calculates a count, so stats is unnecessary and can cause conflict. The top command already calculates a count and sorts, so using stats before top is redundant and can cause unexpected results. The correct approach is to use 'top limit=5 department' directly on the inputlookup without stats.

Answer

The limit parameter in top should be written before the field name

Answer

The sort command should be placed before stats

Answer

The inputlookup should be used with a subsearch

Question 2

A company has a Splunk environment with multiple indexers and a search head. They have a large CSV lookup file for user permissions that is used in many dashboards. Recently, users have reported that dashboards are timing out or slow. The lookup file is about 500 MB and is stored in $SPLUNK_HOME/etc/apps/app_name/lookups/. The lookup is defined as an automatic lookup in props.conf for the source type 'user_activity'. The dashboards use the lookup to enrich events and then perform aggregations. The administrator checks the search logs and sees that searches using the lookup are taking a long time, and some are failing with 'Search head timeout'. The lookup file is updated daily by a script that replaces the file. Which course of action would best improve performance without sacrificing data enrichment?

Accepted Answer

Convert the CSV lookup to a KV Store lookup with the same data. Converting the CSV lookup to a KV Store lookup provides better performance for large lookups. KV Store lookups are indexed and more efficient for large datasets, and they support automatic lookups. Simply using the lookup command in dashboards would not address the size issue, splitting into multiple files adds complexity, and increasing timeout only masks the problem.

Answer

Split the lookup into multiple smaller files and use multiple lookups

Answer

Remove the automatic lookup and use the lookup command only in the dashboards

Answer

Increase the search head timeout setting

Question 3

A security analyst wants to map IP addresses to hostnames using a CSV lookup file. Which command is correct to define a lookup that maps the IP field to hostname field, with the file named 'ip_host.csv'?

Accepted Answer

lookup ip_host.csv ip as ip_output hostname as hostname_output. The lookup command syntax for mapping multiple fields is 'lookup

as

as '. Here, 'lookup ip_host.csv ip as ip_output hostname as hostname_output' correctly maps the ip field from your data to ip_output in the lookup, and hostname from the lookup to hostname_output. Option A incorrectly uses OUTPUT, which is used for single field output. Option B has reversed order and missing output alias. Option C returns all rows without mapping.

Answer

lookup ip_host.csv hostname OUTPUT ip

Answer

lookup ip_host.csv hostname as hostname ip as ip_output

Answer

inputlookup ip_host.csv

Question 4

A dashboard panel uses a timechart to show error counts over time. Users report that the time range picker does not affect the panel. What is the most likely cause?

Accepted Answer

The search uses a fixed earliest and latest time.. If the search uses fixed earliest/latest times (e.g., via `earliest=-30d@d` or a set time range in the search string), the time range picker has no effect. Option A is incorrect because sharing the dashboard does not affect time range behavior. Option B is incorrect because 'stats' can still respect the time range if used correctly, but the issue here is fixed time bounds, not the command. Option C is incorrect because an index that is not time-based would prevent any time-based search from working, but the panel would show no data or an error, not simply ignore the time picker.

Answer

The dashboard is not shared.

Answer

The panel uses 'stats' instead of 'timechart'.

Answer

The index is not time-based.

Question 5

A large lookup file with 10 million rows is used in a search that joins with main index data. The search is slow. Which optimization should be applied first?

Accepted Answer

Convert the lookup to a KV store collection.. Converting a large lookup to a KV store collection significantly improves performance by enabling indexed lookups, reducing the time needed for join operations. Option A is incorrect because 'lookup local=true' only controls where the lookup file is searched (local versus peers), not its performance. Option B is incorrect because adding a filter using a subsearch adds overhead and is not an optimization; it can make the search slower. Option D is incorrect because 'inputlookup' loads the entire lookup into memory, which for 10 million rows would be slow and memory-intensive, not a performance improvement.

Answer

Use 'lookup local=true' to reduce time.

Answer

Add a filter on the lookup using a subsearch.

Answer

Use 'inputlookup' instead of 'lookup'.

Question 6

A lookup definition includes the option 'batch_index_query=True'. What is the effect?

Accepted Answer

The lookup is populated from an index query when first used.. Batch_index_query=True means the lookup is populated from an index search when first used. Option B is wrong because it incorrectly implies batch processing to reduce lookups. Option C is wrong because it incorrectly implies the lookup is applied to all indexes. Option D is wrong because caching is separate.

Answer

The lookup is batch-processed to reduce number of lookups.

Answer

The lookup is applied to all indexes at once.

Answer

The lookup is cached across all search heads.

Question 7

In a dashboard panel, a table shows event counts by source. The user wants to click on a sourcetype to drill down to a new search showing all events from that source. Which token-based drilldown approach is correct?

Accepted Answer

Set a drilldown action to 'search' with a search string containing $row.sourcetype$.. Using $row.sourcetype$ in a drilldown search string passes the clicked value dynamically. Option A is wrong because custom JavaScript is unnecessary and not the recommended token-based approach. Option B is wrong because 'form' action submits form inputs, not simply a token with the clicked value. Option C is wrong because a static link URL cannot dynamically pass the clicked sourcetype.

Answer

Use a custom JavaScript to navigate.

Answer

Set a drilldown action to 'form' and submit the token.

Answer

Set a drilldown action to 'link' with a URL that includes the sourcetype.

Question 8

Which TWO statements about lookup tables are true?

Accepted Answer

A lookup definition can include time-based expiration.. Options B and D are correct. B: A lookup definition can include time-based expiration, allowing lookups to automatically refresh after a specified period. D: Lookups can be defined from CSV files or KV store collections, providing flexibility in data sources. A is false because lookups can be defined by power users and administrators, not just administrators. C is false because lookups are case-insensitive by default, not case-sensitive. E is false because lookups can be used in multiple commands such as 'lookup', 'inputlookup', and 'outputlookup'.

Answer

Lookups can only be defined by administrators.

Answer

Lookups are case-sensitive by default.

Answer

Lookups can only be used in the 'lookup' command.

Question 9

Which THREE factors should be considered when deciding between using a lookup table and a KV store for enriching data?

Accepted Answer

KV store collections can be updated in real-time via REST API.. The correct factors are B, C, and D. B is correct because KV stores can be updated in real-time via REST API, while lookup tables are typically static files. C is correct because KV store collections can be used with the 'kv' command for search-time operations, whereas lookup tables use 'inputlookup' or 'lookup'. D is correct because lookup tables can support time-based lookups using time fields, which is a feature not available in KV stores. A is incorrect because 'inputlookup' is for file-based lookups, not KV stores; KV store collections are typically accessed with the 'kv' command. E is incorrect because KV stores are generally faster and more scalable for large datasets due to their database-backed storage and indexing, while CSV lookup files can become slow when dealing with very large data sets.

Answer

KV store collections can be used with the 'inputlookup' command.

Answer

Lookup tables are faster for large datasets.

Question 10

Which TWO features are available for customizing dashboards in Splunk's Simple XML?

Accepted Answer

Automatically refreshing panels using token 'refresh'.. Options C and D are correct. C: The 'refresh' token in Simple XML allows automatic panel refreshing without user interaction. D: Drilldown actions can be added to tables and charts to enable interactivity, such as linking to other dashboards or searches. A is incorrect because HTML panels in Simple XML cannot embed custom JavaScript; they only support basic HTML. B is incorrect because CSS customization in Simple XML is limited to the dashboard level, not individual panels, and color changes require CSS files or inline styles. E is incorrect because Splunk does not support multiple dashboard versions per user role; role-based access is managed via permissions, not separate dashboard versions.

Answer

Using HTML in a panel to embed custom JavaScript.

Answer

Using CSS to change the color of all panels.

Answer

Creating multiple dashboard versions for different user roles.

Question 11

You are a Splunk administrator at a large e-commerce company with over 5,000 employees and millions of customers. The development team has created a dashboard that displays sales data by region, using a lookup table to map customer IDs to region names. The lookup file, 'customer_region.csv', is stored on the search head. Recently, the lookup table was updated with new customer IDs, but the dashboard continues to show old region names for new customers. You have verified that the lookup file contains the new mappings and that the file is correctly formatted. The dashboard uses the 'lookup' command in its base search. You have also confirmed that the lookup definition in transforms.conf points to the correct file. The lookup file is approximately 100 MB and is updated weekly. The dashboard is accessed by multiple users across the organization. The issue only affects new customers added in the latest update. Old customers still show correct regions. You have checked the file size and timestamp, and the new file is present. The Splunk version is 8.2. The search head is not clustered. No errors are appearing in the splunkd.log related to lookups. The dashboard uses a simple XML with a timechart and a lookup. The search string is: index=sales sourcetype=transactions | lookup customer_region.csv customer_id OUTPUT region | timechart count by region. You have also tried restarting the search head, but the issue persists. What is the most likely cause?

Accepted Answer

The search head is using a cached version of the lookup, and you need to clear the lookups cache.. Splunk caches lookup files on the search head to improve performance. When the lookup file is updated externally, the cache may still serve the old version until it is explicitly cleared or the search head is restarted. In this scenario, the file is correctly formatted and the definition points to the correct file, but the cache still holds the previous version. Clearing the lookup cache forces Splunk to reload the file from disk, resolving the issue. Option A is incorrect because 'batch_index_query' is not related to lookup caching. Option B is incorrect because the dashboard uses the correct lookup name. Option C is incorrect because restarting the search head may not clear the cache; the cache must be cleared explicitly.

Answer

The lookup definition has 'batch_index_query=True' and is not refreshing.

Answer

The dashboard is using the wrong lookup name.

Answer

The lookup file is cached and needs to be reloaded by restarting Splunk.

Question 12

You are a Splunk power user working for a healthcare organization. You have created a visualization that shows patient wait times by department over the last 30 days. The chart uses a timechart command with a 'stacked' option. Recently, the chart started showing negative values for some departments, which is impossible because wait times cannot be negative. You have verified that the raw data is correct and contains only positive wait times. The search is: index=healthcare sourcetype=patient_wait | timechart span=1d avg(wait_time) by department. The chart is displayed as a stacked area chart. The negative values appear only for a few departments sporadically. You suspect the issue is related to how null values are handled. What could be causing the negative values?

Accepted Answer

The 'stacked' option is misinterpreting null values as negative.. In stacked area charts, when there are null values (missing data points), the stacking algorithm can misinterpret them as negative values, causing the chart to show negative areas. This is a known behavior in Splunk's stacked area visualization. Option A is wrong because 'limit=0' in timechart controls the maximum number of series displayed, not the handling of null values. Option B is wrong because overlapping time ranges from indexing delays would cause duplication, not negative values. Option C is wrong because the 'other' category aggregates low-value series and does not cause negative values; it is unrelated to null value misinterpretation.

Answer

The timechart command is using 'limit=0' which causes overcounting of series.

Answer

There is a counting error in the search due to overlapping time ranges from data indexing delays.

Answer

The use of 'other' category in stacked charts can cause negative values when there are many series.

Question 13

You are a Splunk consultant for a financial services firm. They have a large lookup table containing customer account numbers and risk scores. This lookup is used in a critical compliance search that runs every hour. The search is failing with a memory error 'The search coordinator stopped the search due to memory usage'. You have already tried increasing the memory limit for the search via limits.conf, but the error persists. The lookup file is a CSV file of 2GB, with approximately 20 million rows. The search is: index=compliance sourcetype=transactions | lookup risk_scores.csv account_id OUTPUT risk_score | stats avg(risk_score) by transaction_type. The search runs on a single search head with 16GB RAM. The lookup is defined as static. What is the most effective optimization to resolve the memory error?

Accepted Answer

Convert the lookup to a KV store collection and use the 'kv' command in the search.. Converting the static CSV lookup to a KV store collection allows the lookup data to be stored in memory as a key-value store, which is optimized for high-performance lookups and can handle large datasets more efficiently than loading the entire CSV into memory. The KV store uses indexing and can serve lookups without loading the whole file, resolving the memory error. Option A is wrong because using 'inputlookup' with a 'where' clause still loads the entire CSV into memory before filtering, so the memory error persists. Option B is wrong because splitting the lookup into multiple files does not reduce the total memory required; the search still needs to load all files. Option D is wrong because 'lookup local=false' distributes the lookup to indexers, but the indexers would still need to load the CSV into memory, and the search head coordinates the search, which may still cause memory issues. Converting to KV store is the most effective optimization for this scenario.

Answer

Use 'inputlookup' with a 'where' clause to filter the lookup to only relevant account IDs before joining.

Answer

Split the lookup into multiple smaller files and use multiple lookups in the search.

Answer

Use 'lookup local=false' in the search to distribute the lookup to indexers.

Question 14

A user has created a dashboard panel using a 'chart' command with 'datacount by host'. The chart shows counts per host, but the hosts appear in alphabetical order. The user wants to sort the chart by count descending, so that the host with the most events appears first. The search is: index=main sourcetype=access | chart count by host. The dashboard is built using Simple XML. Which approach should be used to achieve the desired sorting?

Accepted Answer

Add '| sort -count' after the chart command in the search.. Adding '| sort -count' after the chart command sorts the results by count in descending order, making the host with the most events appear first. Option A is incorrect because the 'top' command produces a different table format (with count and percent fields) and is not appropriate if the desired output is a chart. Option B is incorrect because 'eventstats' adds a statistical field to events but does not replace the chart command or sort the results; it would require additional steps. Option D is incorrect because the Simple XML chart properties panel does not include a sorting option for chart data; sorting must be performed within the search itself.

Answer

Use the 'top' command instead of 'chart' to automatically sort by count.

Answer

Use 'eventstats' to compute counts and then sort by count.

Answer

Use the chart properties panel in the dashboard editor to set sorting by count descending.

Question 15

You are a Splunk power user at a manufacturing company. You have created a timechart that shows machine temperature readings over time. The data is indexed with timestamps every minute, but the timechart shows gaps where no data exists because some machines may not report at all times. You want to fill the gaps with 0 values to avoid misleading visualizations. The current search is: index=manufacturing sourcetype=temperature | timechart span=1h avg(temp) by machine. Which modification to the timechart command will fill the gaps with 0?

Accepted Answer

timechart span=1h usenull=t. Usenull=t fills null values with 0. Option A is incorrect because cont=t ensures continuous time buckets but does not fill nulls with 0. Option B is incorrect because limit=0 does not affect null filling. Option D is incorrect because usenull=f leaves gaps, and useother=f is irrelevant.

Answer

timechart span=1h cont=t

Answer

timechart span=1h limit=0

Answer

timechart span=1h usenull=f useother=f