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[Table Visualization] Replace table visualization with React and Data…
…Grid (opensearch-project#2863) * [Table Visualization] Replace table visualization with React and DataGrid In this PR, we add back functions to make new table usage to be consistent with the replaced one. * total function * percentage column * filter in/out Meanwhile, we also add back server. Functional tests are removed. We will add new functional test in opensearch-dashboards-functional-test repo. We also clean out some legacy codes. Issue Resolved: opensearch-project#2855 Signed-off-by: Anan Zhuang <ananzh@amazon.com> * add some data-test-subj and fix PR comments Signed-off-by: Anan Zhuang <ananzh@amazon.com> * Fix PR comments and add unit tests Signed-off-by: Anan Zhuang <ananzh@amazon.com> * remove listenOnChange Signed-off-by: Anan Zhuang <ananzh@amazon.com> Signed-off-by: Anan Zhuang <ananzh@amazon.com>
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Contains the data table visualization, that allows presenting data in a simple table format. | ||
# Data Table | ||
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This is an OpenSearch Dashboards plugin that is used to visualize data and aggregations in tabular format. | ||
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## Create Data Table | ||
To create a data table in OpenSearch Dashboards, first select `Visualize` from the navigation menu. Then click `Create Visualization` and choose `Data Table` as the visualization type. | ||
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## Select Metrics | ||
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### Metrics Aggregation | ||
At the `Metrics`, select the metric aggregation type from the menu and configure it accordingly. You could also add multiple metrics and each metrics is a separate column in table visualization. | ||
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### Buckets Aggregation | ||
At the `Buckets`, configure the columns to be displayed in the table visualization. | ||
- `Split Rows` is used when you want to divide one row into more based on some category. It splits one row into multiple and add columns based on the categories you choose to split. For example, if you split the data based on gender then you want to know more on each gender's clothing preference. You could click `Split Rows` and input `clothing.category` in terms. Each gender's data is now split across to multiple rows based on a new added column `clothing.category`. | ||
- `Split Table` splits the table into separate tables for the aggregation you choose. It is similar to `Split Rows`, but this time each row becomes a single table with aggregation columns arranged horizontally or vertically. | ||
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## Select Options | ||
In the `Options` tab, you can configure more options. | ||
- `Max rows per page` is the maximum number of rows displayed per page. | ||
- `Show metrics for every bucket/level` adds metrics aggregation to every column. | ||
- `Show partial rows` will include data with missing columns. | ||
- `Show total` calculates the selected metrics per column and displays the result at the bottom. Warning - depending on your columns and the total aggregation function selected, this may generate statistically invalid results. For example, avoid summing or averaging averages. | ||
- `Percentage column` adds one percentage column based on the chosen metrics aggregation. | ||
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## Example | ||
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Below is an example of creating a table visualization using sample ecommerce data. | ||
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- Create a new data table visualization and set a relative time 15 weeks ago. | ||
- Compute the count of ecommerce: Choose `Count` in Metrics Aggregation. | ||
- Split the rows on the top 5 of `manufacturer.keyword` ordered by `Metric:Count` in descending and add a label "manufacturer". | ||
- Split the table in rows on the top 5 of `geoip.city_name` ordered by `Metric:Count` in ascending order. | ||
- Click the `Save` button on the top left and save the visualization as "Top manufacturers by count per city". | ||
- Choose a table and click the download icon to download the table. |
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