# Amazon Redshift

You can quickly import data from your Amazon Redshift Database into Exploratory.

Here is a [blog post](https://blog.exploratory.io/exploratory-data-analysis-for-amazon-redshift-with-r-dplyr-9a14441020eb#.aqcbfa6h8) introducing this support in detail.

## 1. Create a Connection to use

Create a connection following [this instruction](https://docs.exploratory.io/data_import/database-data/connection).

## 2. Open Redshift Import dialog

Click '+' button next to 'Data Frames' and select 'Database Data'.

![](/files/-M4oN-qBMezITjny_pQQ)

Click Amazon Redshift to select.

![](/files/-M4oN66k4YJQfHTwMU5I)

## 3. Preview and Import

Click Preview button to see the data back from your Redshift db.

![](/files/-M4oN66mzrfS3x8GJpWw)

If it looks ok, then you can click 'Import' to import the data into Exploratory.

## 4. Querying Random Sample Data

You might want to take a random sample of the data that would be reasonable size for your analysis.

You can use [md5](http://docs.aws.amazon.com/redshift/latest/dg/r_MD5.html) function to get random number generated and use it like below to get the random sample of the data.

```
SELECT *
   FROM airline_2016_01
   ORDER BY md5('randomSeed' || flight_num)
   LIMIT 100000
```

## 5. Using Parameters in SQL

First, click a parameter link on the SQL Data Import Dialog.

![](/files/-M4oN2yAtTsqxNt3r0_M)

Second, define a parameter and click Save button.

![](/files/-M4oN2yC4K_GmMFFjzoo)

Finally, you can use @{} to surround a variable name inside the query like below.

```
select *
from airline_2016_01
where carrier = @{carrier}
```

If you type @ then it suggests parameters like below.

![](/files/-M4oN2yEXevqQptAWUEl)

Here's a [blog post](https://exploratory.io/note/kanaugust/An-Introduction-to-Parameter-in-Exploratory-WCO4Vgn7HJ) for more detail.

## 6. AWS Security Group Setup

![](/files/-M4oN66v_0i1voeo7Yp-)

If you encounter a database connection error, please go to AWS console and make sure you added your client PC's IP address to your Security Group (Inbound) associated with the Redshift cluster.

## 7. Number of rows

From performance point of view, we no longer show actual number of rows which can be only fetched by executing whole query again.

![](/files/-M4oN66xWkcCxqo19jUZ)

If you still want to show the actual number of query for your query, you can do so by setting System Configuration.

![](/files/-M4oN66zCHttnANqtQHx)

Then set "Yes" For "Show Actual Number of Rows on SQL Data Import Dialog"

![](/files/-M4oN670aVGCuTHA4oG4)

This will show you Actual Number of Rows like below.

![](/files/-M4oN6725Fzzj5A208wn)

## 8. Exploratory Data Analysis for Amazon Redshift with R & dplyr

Here is the link to the blog post [Exploratory Data Analysis for Amazon Redshift with R & dplyr](https://blog.exploratory.io/exploratory-data-analysis-for-amazon-redshift-with-r-dplyr-9a14441020eb)


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