Data Browser is a WYSIWYG GUI for adding, modifying and viewing your appbase.io app's data.

Data is stored as JSON documents. You can read more about how to model your data over here.

Installation

The data browser is available within appbase.io dashboard. But it can also be:

Creating An App

You can go to the appbase.io dashboard view of your cluster and create an index.

Adding Your First Data

You can access the databrowser from the dashboard view of your cluster or independently via the Dejavu app.

Follow the above steps to add your first data.

Adding New Field

Dejavu now also supports adding new fields, including setting the appropriate mappings for the field.

You have to first be in the Editing mode. And then select the + button near the field name headers in the column display on the top right.

You can pick from the one of the available data types or set your own mapping.

Field Data Types

Field data types are present in one of three shapes:

  1. Primitive: Text, Keyword, Integer, Float, Double, Date, Geo Point, Boolean are some examples.

  2. Array: An array shape in appbase.io is just a container that can hold one or more values of the primitive data type. There is no special data type associated with it.

  3. Object: An object shape in appbase.io acts as a container that can hold a nested JSON object, each keys of which representing a primitive data type or another object / array container.

Beyond the primitive data types, there are also specialized data types that are specific to a search engine, like completion, ip, percolator. You can read all about the supported data types over here.

How to Set Mappings

You can use:

  1. Data Browser: The data browser UI can be used to set mappings via the Add New Field UI button.

The UI supports adding all the primitive types. You can set your own mapping object for creating a specialized type or if you want to set any non-default options within a type.

OR

  1. Schema UI: The Schema view gives you an overall view of your index's fields. You can set a specific use-case, data type, add a new field to the index or remove a field from the index. Read more for the Schema UI docs over here.

OR

  1. REST API: You can use the REST API to set the mappings using the PUT /_mapping endpoint.

Note

Mappings are immutable in Elasticsearch. Once set, they can't be changed.

Operations

Adding Data

The data browser allows adding data as a single JSON object or multiple JSON objects (passed as an array). It is recommended to pass up to 100 objects at a time.

Updating Existing Data

Existing data records can be updated easily. Select a record from the view and tap the Update button.

Deleting Data

Data records can also be deleted easily. Select a record (or multiple) from the view and tap the Delete button.

Importing Data

You can directly import JSON or CSV data files into appbase.io using the data import functionality.

Here is a pic showing import of a JSON file when creating a new app.

The import view lets you set the data mappings via a GUI and index data. Currently, it supports up to 100,000 records at a time (or up to 100 MB of data).

Once your data is imported, you can view the data via the browser view.

Setting a Unique Document ID

When importing a frequently changing dataset, we recommend setting a Unique Id field. This can be enabled by selecting the checkbox for "Does the data have unique id?" question followed by selecting an id column (a Mark as Id column label should appear in the active column).

Setting a Unique Id column ensures that your dataset doesn't create duplicate documents across re-imports.

When is it a good idea to use this feature?

  • Do you frequently update existing documents?
  • Are you importing data from another data source (e.g. MongoDB, Google Analytics) where you already have a unique Id column?
  • Do you plan to interact with the imported data via code?
  • Do you have more than 1,000 documents?

You don't need to use this feature if your documents are never the same or if you are dealing with a very small set of documents.

Expected Formats

JSON

  • Spaces and/or special characters used in field names are automatically replaced with acceptable characters in the import view,
  • The expected shape for the JSON file is an Array of document objects.
Copy 
[
  {
    "field": "value",
    "nested_field": {
      "field": "value"
    },
    "array_field": ["A", "B"]
  },
  {
    ...
  }
]

CSV

  • If you are importing a CSV file, we treat the first row as the column headers row.
  • Spaces and/or special characters used in field names are automatically replaced with acceptable characters in the import view.
  • To set a null value in a specific cell, either leave the cell as empty or explicitly use the null keyword.
  • Column names ending with lat and lon are automatically detected to be of Geopoint datatype.
  • Setting an Array field from a CSV file requires the cell data to be wrapped in "[..]" brackets, e.g. "[key1, key2]". (Note: If you are editing in Excel, the wrapping quotes (") aren't required)
  • Setting a nested field from a CSV file requires using a dot notation, e.g. nested_field.a and nested_field.b column names will be imported as sibling fields a and b within the nested_field field.

Doing more with data

The dashboard offers a great way to get started with appbase.io with importing data and applying search relevancy settings. From here on, you can create a Test UI and start progressively working with analytics, query rules and security features.