Index patterns for time-series in Elasticsearch

Introduction

Index patterns help you organize and search time-based data easily. They let you find data from many time-stamped indexes quickly.

You collect daily logs and want to search across many days.

You monitor system metrics stored in monthly indexes.

You analyze sales data that is saved by week.

You want to visualize trends over time in a dashboard.

You need to filter data by date ranges efficiently.

Syntax

Elasticsearch

PUT /_index_template/template_name
{
  "index_patterns": ["pattern*"],
  "template": {
    "settings": { ... },
    "mappings": { ... }
  }
}

Use wildcards (*) to match multiple indexes by date or name.

Index patterns often include date parts like 'logs-2023.06.*' to cover all June 2023 indexes.

Examples

This creates a template for all logs indexes from June 2023. It sets one shard and defines the timestamp and message fields.

Elasticsearch

PUT /_index_template/logs_template
{
  "index_patterns": ["logs-2023.06.*"],
  "template": {
    "settings": {
      "number_of_shards": 1
    },
    "mappings": {
      "properties": {
        "timestamp": {"type": "date"},
        "message": {"type": "text"}
      }
    }
  }
}

This searches all metrics indexes for June 2023 using the index pattern with a date range filter.

Elasticsearch

GET /metrics-2023.06.*/_search
{
  "query": {
    "range": {
      "timestamp": {
        "gte": "2023-06-01",
        "lt": "2023-07-01"
      }
    }
  }
}

Sample Program

This creates an index template for all 2023 event indexes with two shards and defines event_time and event_type fields. Then it searches all events on June 15, 2023.

Elasticsearch

PUT /_index_template/my_timeseries_template
{
  "index_patterns": ["events-2023.*"],
  "template": {
    "settings": {
      "number_of_shards": 2
    },
    "mappings": {
      "properties": {
        "event_time": {"type": "date"},
        "event_type": {"type": "keyword"}
      }
    }
  }
}

GET /events-2023.06.15/_search
{
  "query": {
    "match_all": {}
  }
}

Important Notes

Index patterns use wildcards (*) to match multiple indexes easily.

Templates help keep settings and mappings consistent for new time-series indexes.

Using date parts in index names helps organize data by time.

Summary

Index patterns group many time-based indexes for easy searching.

Templates define how these indexes are created and structured.

Use wildcards and date formats to match the right indexes.

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