This article explains how to import data directly from Amazon S3 to Arm Treasure Data.
Install Bulk Import
First, install the toolbelt, which includes bulk loader program, on your computer.
After the installation, the
td command will be installed on your computer. Open up the terminal and type
td to execute the command. Also, make sure you have
java as well. Run
td import:jar_update to download the up-to-date version of our bulk loader:
$ td usage: td [options] COMMAND [args] $ java Usage: java [-options] class [args...] $ td import:jar_update Installed td-import.jar 0.x.xx into /path/to/.td/java
Please login to your Treasure Data account.
$ td account -f Enter your Treasure Data credentials. Email: xxxxx Password (typing will be hidden): Authenticated successfully. Use 'td db:create <db_name>' to create a database.
Importing data from Amazon S3
The bulk loader can read data from files stored in Amazon S3 in all three supported file formats:
- CSV (default)
Suppose you have a file called data.csv on Amazon S3 with these contents:
"host","log_name","date_time","method","url","res_code","bytes","referer","user_agent" "18.104.22.168","-","2004-03-07 16:05:49","GET","/twiki/bin/edit/Main/Double_bounce_sender?topicparent=Main.ConfigurationVariables",401,12846,"","" "22.214.171.124","-","2004-03-07 16:06:51","GET","/twiki/bin/rdiff/TWiki/NewUserTemplate?rev1=1.3&rev2=1.2",200,4523,"","" "126.96.36.199","-","2004-03-07 16:10:02","GET","/mailman/listinfo/hsdivision",200,6291,"","" "188.8.131.52","-","2004-03-07 16:11:58","GET","/twiki/bin/view/TWiki/WikiSyntax",200,7352,"",""
Execute the following commands to upload the CSV file:
$ td db:create my_db $ td table:create my_db my_tbl $ td import:auto \ --format csv --column-header \ --time-column date_time \ --time-format "%Y-%m-%d %H:%M:%S" \ --auto-create my_db.my_tbl \ "s3://<s3_access_key>:<s3_secret_key>@/my_bucket/path/to/data.csv"
where the location of the file is expressed as an S3 path with the AWS public and private access keys embedded in it.
|Because `td import:auto` executes MapReduce jobs to check the invalid rows, it'll take at least 1-2 minutes.|
|If the column chosen for `--time-column` is in epoch timestamp (or unix time), you don't need the `--time-format` flag.|
In the above command, we assumed that:
- The CSV files are located on Amazon S3, within a bucket called
my_bucketunder this path/key
- The first line in the file indicates the column names, hence we specify the --column-header option. If the file does not have the column names in the first row, you will have to specify the column names with the --columns option (and optionally the column types with --column-types option), or use the --column-types for each column in the file.
- The time field is called “date_time” and it’s specified with the --time-column option
- The time format is %Y-%m-%d %H:%M:%S and it’s specified with the --time-format option
The source files to be imported by the bulk loader can be specified as full Amazon S3 paths or using wildcards. Here are some examples:
All files under my_bucket/path/to/ with prefix data;
All files under my_bucket/path/to/ with prefix data and extension .csv;
All files under my_bucket/path/to/ with extension .csv;
All files under my_bucket/path/to/;
All files in the direct subfolders of my_bucket/path/ with extension .csv;
All files in all subfolders of my_bucket/path/ with extension .csv;
For further details, check the following pages: