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.