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ECE Practice Exam — Part 2

In Part 2 of the Elastic Certified Engineer practice exam, you will be tested on the following exam objectives: * Perform index, create, read, update, and delete operations on the documents of an index * Use the Reindex API and Update By Query API to reindex and/or update documents * Define and use an ingest pipeline that satisfies a given set of requirements, including the use of Painless to modify documents * Diagnose Shard Issues and Repair a Cluster’s Health * Write and execute a search query for terms and/or phrases in one or more fields of an index * Write and execute a search query that is a Boolean combination of multiple queries and filters * Highlight the search terms in the response of a query * Sort the results of a query by a given set of requirements * Implement pagination in the results of a search query * Apply fuzzy matching to a query * Define and Use a Search Template * Write and execute a query that searches multiple clusters * Write and execute metric and bucket aggregations * Write and execute aggregations that contain sub-aggregations * Write and execute pipeline aggregations * Back up and restore a cluster and/or specific indices * Configure a cluster for cross-cluster search

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Path Info

Level

Advanced

Duration

4h 0m

Published

Jan 10, 2020

Challenge

Diagnose and Repair the "c1" cluster.
Start Elasticsearch

Using the Secure Shell (SSH), log in to the c1-data-1 node as cloud_user via the public IP address.

Become the elastic user:
```
sudo su - elastic
```
Start Elasticsearch as a daemon:
```
/home/elastic/elasticsearch/bin/elasticsearch -d -p pid
```
Replicate the logs index

Use the Kibana console tool on the c1 cluster to execute the following:
```
PUT logs/_settings
{
  "number_of_replicas": 1
}
```
Reduce the shakespeare index's replication

Use the Kibana console tool on the c1 cluster to execute the following:
```
PUT shakespeare/_settings
{
  "number_of_replicas": 1
}
```
Remove allocation filtering for the bank index

Use the Kibana console tool on the c1 cluster to execute the following:
```
PUT bank/_settings
{
  "index.routing.allocation.require._name": null
}
```
Challenge

Transfer the "bank" index to the "c2" cluster.
Configure the c2 cluster to remote reindex from the c1 cluster

Using the Secure Shell (SSH), log in to the c2 cluster nodes as cloud_user via the public IP address.

Become the elastic user:
```
sudo su - elastic
```
Add the following line to /home/elastic/elasticsearch/config/elasticsearch.yml:
```
reindex.remote.whitelist: "10.0.1.101:9200, 10.0.1.102:9200, 10.0.1.103:9200, 10.0.1.104:9200"
```
Stop Elasticsearch:
```
pkill -F /home/elastic/elasticsearch/pid
```
Start Elasticsearch as a background daemon and record the PID to a file:
```
/home/elastic/elasticsearch/bin/elasticsearch -d -p pid
```
Create the bank index on the c2 cluster

Use the Kibana console tool on the c2 cluster to execute the following:
```
PUT bank
{
  "settings": {
    "number_of_shards": 1,
    "number_of_replicas": 0
  }
}
```
Reindex the bank index on the c2 cluster

Use the Kibana console tool on the c2 cluster to execute the following:
```
POST _reindex
{
  "source": {
    "remote": {
      "host": "http://10.0.1.101:9200",
      "username": "elastic",
      "password": "la_elastic_409"
    },
    "index": "bank"
  },
  "dest": {
    "index": "bank"
  }
}
```
Delete the bank index on the c1 cluster

Use the Kibana console tool on the c1 cluster to execute the following:
```
DELETE bank
```
Challenge

Backup the "bank" index on the "c2" cluster.
Configure the nodes

Using the Secure Shell (SSH), log in to the c2-master-1 node as cloud_user via the public IP address.

Become the elastic user:
```
sudo su - elastic
```
Create the repo directory:
```
mkdir /home/elastic/snapshots
```
Add the following line to /home/elastic/elasticsearch/config/elasticsearch.yml:
```
path.repo: "/home/elastic/snapshots"
```
Stop Elasticsearch:
```
pkill -F /home/elastic/elasticsearch/pid
```
Start Elasticsearch as a background daemon and record the PID to a file:
```
/home/elastic/elasticsearch/bin/elasticsearch -d -p pid
```
Create the local_repo repository

Use the Kibana console tool on the c2 cluster to execute the following:
```
PUT _snapshot/local_repo
{
  "type": "fs",
  "settings": {
    "location": "/home/elastic/snapshots"
  }
}
```
Backup the bank index

Use the Kibana console tool on the c2 cluster to execute the following:
```
PUT _snapshot/local_repo/bank_1?wait_for_completion=true
{
  "indices": "bank", 
  "include_global_state": true
}
```

Challenge

Configure Cross-Cluster Search.

Use the Kibana console tool on the c1 cluster to execute the following:

PUT _cluster/settings
{
  "persistent": {
    "cluster": {
      "remote": {
        "c2": {
          "seeds": [
            "10.0.1.105:9300"
          ]
        }
      }
    }
  }
}

Challenge

Create, Update, and Delete Documents.

Delete the `bank` documents

Use the Kibana console tool on the c2 cluster to execute the following:

DELETE bank/_doc/5
DELETE bank/_doc/27
DELETE bank/_doc/819

Update the `bank` document

Use the Kibana console tool on the c2 cluster to execute the following:

POST bank/_update/67
{
  "doc": {
    "lastname": "Alonso"
  }
}

Create the `bank` document

Use the Kibana console tool on the c2 cluster to execute the following:

PUT bank/_doc/1000
{
  "account_number": 1000,
  "balance": 35550,
  "firstname": "Stosh",
  "lastname": "Pearson",
  "age": 45,
  "gender": "M",
  "address": "125 Bear Creek Pkwy",
  "employer": "Linux Academy",
  "email": "[email protected]",
  "city": "Keller",
  "state": "TX"
}

Update the `shakespeare` mapping

Use the Kibana console tool on the c1 cluster to execute the following:

PUT shakespeare/_mappings
{
  "properties": {
    "line_id": {
      "type": "integer"
    },
    "line_number": {
      "type": "text",
      "fields": {
        "keyword": {
          "type": "keyword",
          "ignore_above": 256
        }
      }
    },
    "play_name": {
      "type": "keyword"
    },
    "speaker": {
      "type": "keyword"
    },
    "speech_number": {
      "type": "integer"
    },
    "text_entry": {
      "type": "text",
      "fields": {
        "english": {
          "type": "text",
          "analyzer": "english"
        },
        "keyword": {
          "type": "keyword",
          "ignore_above": 256
        }
      }
    },
    "type": {
      "type": "text",
      "fields": {
        "keyword": {
          "type": "keyword",
          "ignore_above": 256
        }
      }
    }
  }
}

Delete and update the `shakespeare` documents

Use the Kibana console tool on the c1 cluster to execute the following:

POST shakespeare/_update_by_query
{
  "script": {
    "lang": "painless",
    "source": """
      if (ctx._source.line_number == "") {
        ctx.op = "delete"
      }
    """
  }
}

Create the ingest pipeline

Use the Kibana console tool on the c1 cluster to execute the following:

PUT _ingest/pipeline/fix_logs
{
  "processors": [
    {
      "remove": {
        "field": "@message"
      }
    },
    {
      "split": {
        "field": "spaces",
        "separator": "\\s+"
      }
    },
    {
      "script": {
        "lang": "painless",
        "source": "ctx.relatedContent_count = ctx.relatedContent.length"
      }
    },
    {
      "uppercase": {
        "field": "extension"
      }
    }
  ]
}

Create the `logs_new` index

Use the Kibana console tool on the c1 cluster to execute the following:

PUT logs_new
{
  "settings": {
    "number_of_shards": 2,
    "number_of_replicas": 1
  }
}

Reindex the `logs` documents

Use the Kibana console tool on the c1 cluster to execute the following:

POST _reindex
{
  "source": {
    "index": "logs"
  },
  "dest": {
    "index": "logs_new",
    "pipeline": "fix_logs"
  }
}

Challenge

Search Documents.

Search the `bank` index

Use the Kibana console tool on the c1 cluster to execute the following:

GET c2:bank/_search
{
  "from": 0,
  "size": 50,
  "sort": [
    {
      "age": {
        "order": "asc"
      }
    },
    {
      "balance": {
        "order": "desc"
      }
    },
    {
      "lastname.keyword": {
        "order": "asc"
      }
    }
  ], 
  "query": {
    "bool": {
      "must": [
        {
          "term": {
            "gender.keyword": {
              "value": "F"
            }
          }
        },
        {
          "range": {
            "balance": {
              "gt": 10000
            }
          }
        }
      ],
      "must_not": [
        {
          "terms": {
            "state.keyword": ["PA", "VA", "IL"]
          }
        }
      ],
      "filter": {
        "range": {
          "age": {
            "gte": 18,
            "lte": 35
          }
        }
      }
    }
  }
}

Search the `shakespeare` index

Use the Kibana console tool on the c1 cluster to execute the following:

GET shakespeare/_search
{
  "from": 0,
  "size": 20, 
  "highlight": {
    "pre_tags": "<b>",
    "post_tags": "</b>",
    "fields": {
      "text_entry.english": {}
    }
  },
  "query": {
    "bool": {
      "should": [
        {
          "match": {
            "text_entry.english": "life"
          }
        },
        {
          "match": {
            "text_entry.english": "love"
          }
        },
        {
          "match": {
            "text_entry.english": "death"
          }
        }
      ],
      "minimum_should_match": 2
    }
  }
}

Search the `logs` index

Use the Kibana console tool on the c1 cluster to execute the following:

GET logs/_search
{
  "highlight": {
    "fields": {
      "relatedContent.twitter:description": {},
      "relatedContent.twitter:title": {}
    }
  },
  "query": {
    "bool": {
      "must": [
        {
          "match": {
            "relatedContent.twitter:description": {
              "query": "never",
              "fuzziness": 2
            }
          }
        },
        {
          "match_phrase": {
            "relatedContent.twitter:title": "Golden State"
          }
        }
      ]
    }
  }
}

Challenge

Aggregate Documents.

Aggregate on the `bank` index

Use the Kibana console tool on the c1 cluster to execute the following:

GET c2:bank/_search
{
  "size": 0, 
  "aggs": {
    "state": {
      "terms": {
        "field": "state.keyword",
        "size": 5,
        "order": {
          "avg_balance": "desc"
        }
      },
      "aggs": {
        "avg_balance": {
          "avg": {
            "field": "balance"
          }
        }
      }
    }
  },
  "query": {
    "range": {
      "age": {
        "gte": 30
      }
    }
  }
}

Aggregate on the `shakespeare` index

Use the Kibana console tool on the c1 cluster to execute the following:

GET shakespeare/_search
{
  "size": 0, 
  "aggs": {
    "plays": {
      "terms": {
        "field": "play_name",
        "size": 10
      },
      "aggs": {
        "speakers": {
          "cardinality": {
            "field": "speaker"
          }
        }
      }
    },
    "most_parts": {
      "max_bucket": {
        "buckets_path": "plays>speakers"
      }
    }
  }
}

Aggregate on the `logs` index

Use the Kibana console tool on the c1 cluster to execute the following:

GET logs/_search
{
  "size": 0,
  "aggs": {
    "hour": {
      "date_histogram": {
        "field": "@timestamp",
        "calendar_interval": "hour"
      },
      "aggs": {
        "clients": {
          "cardinality": {
            "field": "clientip.keyword"
          }
        },
        "cumulative_clients": {
          "cumulative_sum": {
            "buckets_path": "clients"
          }
        },
        "clients_per_minute": {
          "derivative": {
            "buckets_path": "cumulative_clients",
            "unit": "1m"
          }
        }
      }
    },
    "peak": {
      "max_bucket": {
        "buckets_path": "hour>clients"
      }
    }
  },
  "query": {
    "range": {
      "@timestamp": {
        "gte": "2015-05-19",
        "lt": "2015-05-20",
        "format": "yyyy-MM-dd"
      }
    }
  }
}

Challenge

Create the Search Template.

Use the Kibana console tool on the c2 cluster to execute the following:

POST _scripts/accounts_search
{
  "script": {
    "lang": "mustache",
    "source": {
      "from": "{{from}}{{^from}}0{{/from}}",
      "size": "{{size}}{{^size}}25{{/size}}",
      "query": {
        "bool": {
          "must": [
            {
              "wildcard": {
                "firstname.keyword": "{{first_name}}{{^first_name}}*{{/first_name}}"
              }
            },
            {
              "wildcard": {
                "lastname.keyword": "{{last_name}}{{^last_name}}*{{/last_name}}"
              }
            }
          ]
        }
      }
    }
  }
}

Author

A Cloud Guru

The Cloud Content team comprises subject matter experts hyper focused on services offered by the leading cloud vendors (AWS, GCP, and Azure), as well as cloud-related technologies such as Linux and DevOps. The team is thrilled to share their knowledge to help you build modern tech solutions from the ground up, secure and optimize your environments, and so much more!

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ECE Practice Exam — Part 2

Path Info

Table of Contents

Diagnose and Repair the "c1" cluster.

Start Elasticsearch

Replicate the logs index

Reduce the shakespeare index's replication

Remove allocation filtering for the bank index

Transfer the "bank" index to the "c2" cluster.

Configure the c2 cluster to remote reindex from the c1 cluster

Create the bank index on the c2 cluster

Reindex the bank index on the c2 cluster

Delete the bank index on the c1 cluster

Backup the "bank" index on the "c2" cluster.

Configure the nodes

Create the local_repo repository

Backup the bank index

Configure Cross-Cluster Search.

Create, Update, and Delete Documents.

Delete the bank documents

Update the bank document

Create the bank document

Update the shakespeare mapping

Delete and update the shakespeare documents

Create the ingest pipeline

Create the logs_new index

Reindex the logs documents

Search Documents.

Search the bank index

Search the shakespeare index

Search the logs index

Aggregate Documents.

Aggregate on the bank index

Aggregate on the shakespeare index

Aggregate on the logs index

Create the Search Template.

What's a lab?

Provided environment for hands-on practice

Guided walkthrough

Did you know?

Start learning by doing today

Replicate the `logs` index

Reduce the `shakespeare` index's replication

Remove allocation filtering for the `bank` index

Configure the `c2` cluster to remote reindex from the `c1` cluster

Create the `bank` index on the `c2` cluster

Reindex the `bank` index on the `c2` cluster

Delete the `bank` index on the `c1` cluster

Create the `local_repo` repository

Backup the `bank` index

Delete the `bank` documents

Update the `bank` document

Create the `bank` document

Update the `shakespeare` mapping

Delete and update the `shakespeare` documents

Create the `logs_new` index

Reindex the `logs` documents

Search the `bank` index

Search the `shakespeare` index

Search the `logs` index

Aggregate on the `bank` index

Aggregate on the `shakespeare` index

Aggregate on the `logs` index