Why data pipelines feed Elasticsearch - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to insert a document into Elasticsearch.

Elasticsearch

POST /my_index/_doc/[1]
{
  "user": "alice",
  "message": "Hello Elasticsearch"
}

Drag options to blanks, or click blank then click option'

A1

Bindex

Csearch

Ddelete

Attempts:

3 left

💡 Hint

Common Mistakes

Using operation names like 'index' or 'search' instead of a document ID.

The number 1 is the document ID used to insert the document into the index.

2fill in blank

medium

Complete the code to query documents containing the word 'error'.

Elasticsearch

GET /logs/_search
{
  "query": {
    "match": {
      "message": "[1]"
    }
  }
}

Drag options to blanks, or click blank then click option'

Awarning

Bdebug

Cinfo

Derror

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing unrelated keywords like 'info' or 'debug'.

The query searches for documents where the message field contains the word error.

3fill in blank

hard

Fix the error in the pipeline configuration to send data to Elasticsearch.

Elasticsearch

output {
  elasticsearch {
    hosts => ["[1]"]
    index => "logs-%{+YYYY.MM.dd}"
  }
}

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A9200

Bhttp://localhost:9200

Clocalhost:9200

Dhttp://localhost

Attempts:

3 left

💡 Hint

Common Mistakes

Omitting 'http://' or the port number.

The hosts setting requires the full URL including the protocol, like http://localhost:9200.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps words to their lengths only if length is greater than 3.

Elasticsearch

{word: [1] for word in words if [2]

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Alen(word)

Blen(word) > 3

Cword.startswith('a')

Dword == 'test'

Attempts:

3 left

💡 Hint

Common Mistakes

Using conditions unrelated to length or wrong expressions in the value part.

The comprehension maps each word to its length using len(word) and filters words with length greater than 3 using len(word) > 3.

5fill in blank

hard

Fill all three blanks to create a filtered dictionary from data where keys are uppercase and values are positive.

Elasticsearch

{ [1]: [2] for [3], v in data.items() if v > 0 }

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Ak.upper()

Bv

Ck

Dvalue

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong variable names or not uppercasing keys.

The dictionary comprehension uses k.upper() as keys, v as values, and iterates over k, v pairs from data.items().