Index patterns for time-series in Elasticsearch - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

Identify the correct index pattern for daily logs

You have daily log data indexed in Elasticsearch with indices named like logs-2024.06.01, logs-2024.06.02, and so on. Which index pattern will correctly match all daily log indices for June 2024?

A logs-2024.06.*

B logs-2024.06.01

C logs-2024.*

D logs-*

💡 Hint

Think about how wildcards match parts of the index name.

The pattern logs-2024.06.* matches all indices starting with 'logs-2024.06.' followed by any characters, which includes all daily indices in June 2024. Other options either match only one day, all months, or all logs regardless of date.

🧠 Conceptual

intermediate

Purpose of using time-based index patterns

Why do Elasticsearch users often create index patterns based on time intervals (like daily or monthly indices) for time-series data?

A To reduce the number of shards per index to zero

B To avoid using wildcards in queries

C To improve query performance and manage data retention easily

D To store all data in a single large index for simplicity

💡 Hint

Think about how time-based data grows and how Elasticsearch handles large datasets.

Time-based index patterns allow splitting data into manageable chunks, improving query speed by targeting relevant indices and enabling easy deletion of old data. Other options are incorrect because shards cannot be zero, wildcards are still used, and a single large index can hurt performance.

📝 Syntax

advanced

Find the syntax error in this index pattern

Which option contains a syntax error in the Elasticsearch index pattern for matching monthly indices named like metrics-2024.05, metrics-2024.06?

A metrics-2024.0{5,6}

B metrics-2024.0[56]

C metrics-2024.0[5-6]

D metrics-2024.0*

💡 Hint

Elasticsearch index patterns support wildcards and character classes but not curly brace expansions.

Option A uses curly braces {5,6} which is not supported in Elasticsearch index patterns and causes a syntax error. Options B and C use valid character classes, and D uses a wildcard.

❓ optimization

advanced

Optimizing queries with time-based index patterns

You want to query logs from the last 7 days only. Which index pattern will optimize the query by limiting the indices searched?

A logs-*

B logs-2024.06.0[1-7]

C logs-2024.06.*

D logs-2024.06.0?

💡 Hint

Choose the pattern that matches only the needed days, not the whole month or all logs.

Option B matches only the indices for days 1 to 7 in June 2024, reducing the number of indices queried and improving performance. Option B matches all logs, C matches the whole month, and B matches days 1 to 9 but is less precise.

🔧 Debug

expert

Why does this time-series query return no results?

You run a query on index pattern metrics-2024.06.* but get no results, even though you know data exists for June 1 and June 2. The indices are named metrics-2024.06.01 and metrics-2024.06.02. What is the most likely cause?

A The wildcard * does not match dots in index names

B The indices are closed and not searchable

C The index pattern uses a dot (.) which is not allowed in Elasticsearch index patterns

D The query time range does not include the dates of the indices

💡 Hint

Check if the query time filter matches the data dates.

If the query's time filter does not cover June 1 and June 2, no data will be returned even if the index pattern matches. Dots are allowed in index patterns, and wildcards do match dots. Closed indices would cause errors or no data but are less likely than a time range mismatch.

Practice

1. What is the main purpose of using index patterns in Elasticsearch for time-series data?

easy

A. To group multiple time-based indexes for easier searching

B. To store data permanently without deletion

C. To create visual dashboards automatically

D. To encrypt data in the indexes

Solution

1. Step 1: Understand index patterns role

   Index patterns help combine many time-based indexes so you can search them all at once.

2. Step 2: Compare options

   Only grouping multiple time-based indexes matches the main purpose; others are unrelated.

3. Final Answer:

   To group multiple time-based indexes for easier searching -> Option A

4. Quick Check:

   Index patterns = group time-based indexes [OK]

Hint: Index patterns group many indexes by time for easy search [OK]

Common Mistakes:

• Thinking index patterns store data permanently
• Confusing index patterns with dashboards
• Assuming index patterns encrypt data

2. Which of the following is the correct syntax for an index pattern matching daily logs from January 2024 in Elasticsearch?

easy

A. logs-2024.01.*

B. logs-2024-01-*

C. logs_2024-01-*

D. logs-01-2024-*

Solution

1. Step 1: Identify date format in index pattern

   Elasticsearch uses dash-separated date parts like YYYY-MM-DD, so logs-2024-01-* matches daily logs in January 2024.

2. Step 2: Check other options

   logs-2024.01.* uses dots instead of dashes, which is incorrect. logs_2024-01-* uses underscore instead of dash. logs-01-2024-* has wrong order of date parts.

3. Final Answer:

   <code>logs-2024-01-*</code> -> Option B

4. Quick Check:

   Date format YYYY-MM-DD with dashes = logs-2024-01-* [OK]

Hint: Use dashes YYYY-MM-DD in index patterns for dates [OK]

Common Mistakes:

• Using dots instead of dashes in date format
• Mixing underscores and dashes incorrectly
• Reordering date parts wrongly

3. Given the index pattern metrics-2023.12.* and indexes metrics-2023.12.01, metrics-2023.11.30, metrics-2023.12.15, which indexes will match the pattern?

medium

A. metrics-2023.11.30 only

B. All three indexes

C. metrics-2023.12.01 and metrics-2023.12.15

D. None of the indexes

Solution

1. Step 1: Understand the pattern metrics-2023.12.*

   This pattern matches indexes starting with 'metrics-2023.12.' followed by anything, so it matches December 2023 indexes.

2. Step 2: Check each index

   metrics-2023.12.01 and metrics-2023.12.15 match December 2023; metrics-2023.11.30 is November, so it does not match.

3. Final Answer:

   <code>metrics-2023.12.01</code> and <code>metrics-2023.12.15</code> -> Option C

4. Quick Check:

   Pattern matches December indexes only = metrics-2023.12.01 and metrics-2023.12.15 [OK]

Hint: Wildcards match only after specified prefix [OK]

Common Mistakes:

• Assuming wildcard matches all months
• Ignoring exact prefix before wildcard
• Confusing dot and dash separators

4. You created an index pattern logs-2023-1* to match logs from January 2023, but it also matches October and November indexes. What is the likely mistake?

medium

A. The dash (-) should be a dot (.) in the pattern

B. Index patterns cannot match months, only years

C. The pattern should be logs-2023-1? instead of *

D. Using wildcard * after 1 matches months starting with 1 and 10

Solution

1. Step 1: Analyze wildcard usage in logs-2023-1*

   The wildcard * matches any characters after '1', so it matches '1...' (January) but also '10', '11' because '10' and '11' start with '1' in pattern matching.

2. Step 2: Understand why October and November match

   Because the pattern matches any string starting with '1', it also matches '10' and '11' incorrectly.

3. Final Answer:

   Using wildcard * after 1 matches months starting with 1 and 10 -> Option D

4. Quick Check:

   Wildcard * after 1 matches more than intended = Using wildcard * after 1 matches months starting with 1 and 10 [OK]

Hint: Wildcard * matches any characters, not just one digit [OK]

Common Mistakes:

• Thinking * matches only one character
• Confusing dash and dot separators
• Believing index patterns can't match months

5. You want to create an index pattern that matches all daily indexes for the year 2024 named like events-2024-03-15. Which pattern correctly matches all days in March 2024 but excludes other months?

hard

A. events-2024-03-??

B. events-2024-03-* and events-2024-04-*

C. events-2024-03-??*

D. events-2024-03-*

Solution

1. Step 1: Understand pattern to match daily dates

   Daily indexes have two-digit day numbers, so ?? matches exactly two characters (days 01 to 31).

2. Step 2: Compare options

   events-2024-03-* uses *, which matches any length, possibly including invalid days. events-2024-03-?? uses ?? to match exactly two digits. events-2024-03-??* allows extra characters after two digits, which is incorrect. events-2024-03-* and events-2024-04-* includes April, which should be excluded.

3. Final Answer:

   <code>events-2024-03-??</code> -> Option A

4. Quick Check:

   Two-question marks match exact two-digit days = events-2024-03-?? [OK]

Hint: Use ?? to match exactly two characters (days) in index pattern [OK]

Common Mistakes:

• Using * which matches any length, not exact days
• Including extra months by mistake
• Using patterns that allow invalid day formats