# HOW TO GET THE MAPPINGS TO BE LIKE kibana\_sample\_data\_flights

**URL:** <https://discuss.elastic.co/t/how-to-get-the-mappings-to-be-like-kibana-sample-data-flights/219720>\
**Category:** Kibana\
**Created:** [February 18, 2020, 6:58am UTC](https://discuss.elastic.co/t/how-to-get-the-mappings-to-be-like-kibana-sample-data-flights/219720 "2020-02-18T06:58:18Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![richylyq](https://avatars.discourse-cdn.com/v4/letter/r/41988e/32.png) [@richylyq](https://discuss.elastic.co/u/richylyq)\
**Post date:** [February 18, 2020, 6:58am UTC](https://discuss.elastic.co/t/how-to-get-the-mappings-to-be-like-kibana-sample-data-flights/219720/1 "2020-02-18T06:58:19Z")

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I am using the FSCrawler library by @dadoonet and it works great for the ingestion of data  
But after the ingestion, I cannot seem to use the data for any visualization. Therefore I would like to see how to get the mapping of the job to be somewhat similar with kibana\_sample\_data\_flights.

What I see for kibana\_sample\_data\_flights

```
{
  "kibana_sample_data_flights" : {
    "mappings" : {
      "properties" : {
        "AvgTicketPrice" : {
          "type" : "float"
        },
        "Cancelled" : {
          "type" : "boolean"
        },
        "Carrier" : {
          "type" : "keyword"
        },
        "Dest" : {
          "type" : "keyword"
        },
        "DestAirportID" : {
          "type" : "keyword"
        },
        "DestCityName" : {
          "type" : "keyword"
        },
        "DestCountry" : {
          "type" : "keyword"
        },
        "DestLocation" : {
          "type" : "geo_point"
        },
        "DestRegion" : {
          "type" : "keyword"
        },
        "DestWeather" : {
          "type" : "keyword"
        },
        "DistanceKilometers" : {
          "type" : "float"
        },
        "DistanceMiles" : {
          "type" : "float"
        },
        "FlightDelay" : {
          "type" : "boolean"
        },
        "FlightDelayMin" : {
          "type" : "integer"
        },
        "FlightDelayType" : {
          "type" : "keyword"
        },
        "FlightNum" : {
          "type" : "keyword"
        },
        "FlightTimeHour" : {
          "type" : "keyword"
        },
        "FlightTimeMin" : {
          "type" : "float"
        },
        "Origin" : {
          "type" : "keyword"
        },
        "OriginAirportID" : {
          "type" : "keyword"
        },
        "OriginCityName" : {
          "type" : "keyword"
        },
        "OriginCountry" : {
          "type" : "keyword"
        },
        "OriginLocation" : {
          "type" : "geo_point"
        },
        "OriginRegion" : {
          "type" : "keyword"
        },
        "OriginWeather" : {
          "type" : "keyword"
        },
        "dayOfWeek" : {
          "type" : "integer"
        },
        "timestamp" : {
          "type" : "date"
        }
      }
    }
  }
}

```

But mine is something like this

```
{
  "json" : {
    "mappings" : {
      "properties" : {
        "compatibility" : {
          "properties" : {
            "count" : {
              "type" : "long"
            },
            "score" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "text" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            }
          }
        },
        "count" : {
          "type" : "integer"
        },
        "criteria" : {
          "properties" : {
            "count" : {
              "type" : "long"
            },
            "score" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "text" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            }
          }
        },
        "diophantine" : {
          "properties" : {
            "count" : {
              "type" : "long"
            },
            "score" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "text" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            }
          }
        },
        "linear constraints" : {
          "properties" : {
            "count" : {
              "type" : "long"
            },
            "score" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "text" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            }
          }
        },
        "linear diophantine equations" : {
          "properties" : {
            "count" : {
              "type" : "long"
            },
            "score" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "text" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            }
          }
        },
        "natural numbers" : {
          "properties" : {
            "count" : {
              "type" : "long"
            },
            "score" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "text" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            }
          }
        },
        "nonstrict inequations" : {
          "properties" : {
            "count" : {
              "type" : "long"
            },
            "score" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "text" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            }
          }
        },
        "score" : {
          "type" : "float"
        },
        "strict inequations" : {
          "properties" : {
            "count" : {
              "type" : "long"
            },
            "score" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "text" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            }
          }
        },
        "systems" : {
          "properties" : {
            "count" : {
              "type" : "long"
            },
            "score" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "text" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            }
          }
        },
        "text" : {
          "type" : "text"
        },
        "the set" : {
          "properties" : {
            "count" : {
              "type" : "long"
            },
            "score" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            },
            "text" : {
              "type" : "text",
              "fields" : {
                "keyword" : {
                  "type" : "keyword",
                  "ignore_above" : 256
                }
              }
            }
          }
        }
      }
    }
  }
}
```

---

<div class="post-metadata">

**Author:** ![wylie](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/wylie/32/81794_2.png) [@wylie](https://discuss.elastic.co/u/wylie)\
**Post date:** [February 18, 2020, 3:06pm UTC](https://discuss.elastic.co/t/how-to-get-the-mappings-to-be-like-kibana-sample-data-flights/219720/2 "2020-02-18T15:06:31Z")

</div>

This might be better asked in the Elasticsearch forums, but the basic answer is that your mapping reflects a different type of document. The documents for the sample data are flat, but your mapping reflects that you have objects inside the document. Kibana can handle both of these mappings.

The biggest difference is that Kibana does not visualize full-text data. You should add `keyword` mappings to use text in visualizations.

---

<div class="post-metadata">

**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [March 17, 2020, 3:06pm UTC](https://discuss.elastic.co/t/how-to-get-the-mappings-to-be-like-kibana-sample-data-flights/219720/3 "2020-03-17T15:06:35Z")

</div>

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