Chunk data import / Incremental Import in Sqoop

Recently I faced an issue while importing data from oracle with Sqoop. So far it was working fine till I faced a new requirement. Before discussing about the new requirement, let me quickly write about how it's currently working.

Currently I am running Sqoop from Oozie but I am not using coordinator job. So I am executing each Oozie job manually from command prompt.

You can check these links if you want to know how to run Sqoop and Oozie together.

• Basic Sqoop Import and Export
• Simple Oozie workflow for Sqoop

In our option parameter file, I have a field something like this below:

--where
ID <= 1000000

For each run, I used to change that field manually and re-run my Oozie job.

New Requirement

Now, what I have asked to do is run my Oozie job through coordinator and import block-wise/chunk data from Oracle. Based on the current requirement, what I'm trying to achieve is to import list of rows from M to N. Ideally for each run, I'm targeting to import 15 millions rows from that specific table and Hadoop will process those records and will be ready to process another batch before the following run.

As an example:
1st run: 1 to 20
2nd run: 21 to 40
3rd run: 41 to 60
and so on...

First thing which I started exploring is to use "--boundary-query" parameter which comes with sqoop. From their documents: "By default sqoop will use query select min(<split-by>), max(<split-by>) from <table name> to find out boundaries for creating splits. In some cases this query is not the most optimal so you can specify any arbitrary query returning two numeric columns using --boundary-query argument."

After spending some time on it and discussing in Sqoop mailing list, I came to know that incremental import is not working with chunks. It imports everything since last import (more specifically, everything from --last-value to end).

Then I decided to create a shell action in Oozie which will update the appropriate parameter after each execution of Sqoop, so that following Sqoop runs will have a new options for its import.

So I made some changes in my option parameter file (option.par) and here is the new one:
To store current index value and chunk-size, I used another property based file import.properties:
My shell script will update the value of startIndex by the chunkSize. Here is the script (script.sh) which I wrote for this:

I want to add something here is that when you are modifying a file by a script and running through Oozie, a cache version of the file in HDFS actually being updated. That's why I had to copy back those files to my original location of HDFS. Again, behind the scene, a mapred user is doing the work but I'm running the oozie job as ambari_qa user (note: I'm using Hortonworks Hadoop, HDP 1.2.0). That's why I had to give back all the permissions on those files to all users.

Here is my Oozie workflow (workflow.xml):
I put everything inside my Oozie application path in HDFS. Here is my folder structure:
Don't forget to give the "write" permission when you first put it inside HDFS. Now you can run the Oozie workflow by executing this:

[ambari_qa@ip-10-0-0-91 ~]$ oozie job -oozie http://ip-10-0-0-91:11000/oozie -config job.properties -run

Here is the job.properties file:

This is it! Now every time you execute the Oozie job, it will import a new chunk of data from Oracle. How I'm running it as a coordinator job, I will put them in another post. Jarcec mentioned in one of the Sqoop user mail threads that Sqoop will have this feature soon but I'm not sure it's time frame. So I had to do this work around. It worked for me, I hope it will work for you too!

Note: For privacy purpose, I had to modify several lines on this post from my original post. So if you find something is not working or facing any issues, please do not hesitate to contact me.

Sqoop import/export from/to Oracle

I love Sqoop! It's a fun tool to work with and it's very powerful. Importing and exporting data from/to Oracle by Sqoop is pretty straightforward. One crucial thing you need to remember when working with Sqoop and Oracle together, that is using all capital letters for Oracle table names. Otherwise, Sqoop will not recognize Oracle tables.

This is my database (Oracle) related information:

• URL: 10.0.0.24
• db_name (SID): test
• Schema: Employee_Reporting
• Username: username1
• Password: password1
• Tablename: employee ( I'm going to export this table to HDFS by Sqoop)

Import from Oracle to HDFS:

Let's go through this option file (option.par):

You can see most of the parameters are self-explanatory. Notice that I'm providing table name in all capital letters. How you want to see the imported columns in HDFS? For that, we need to use --fields-terminated-by parameter. Here I'm passing "\t" for that parameter, which means that the column or field for each rows will be tab delimited after import. Sqoop will generate a class(with a list of setter and getter) to invoke the employee object, the name of that class name is defined by --class-name parameter. So in this case, it will create a class named Employee.java inside com.example.reporting package. I'm using --verbose parameter to print out information while Sqoop is working. It's not mandatory and you can ignore it if you want. --split-by parameter represents the name of the column which I want to use for splitting the import data. Here, ID is the primary key of the table Employee. You can use any WHERE clause for your import, in that case you need to pass that with the --where parameter. For the above example, it will import all rows from the table Employee where ID is less than or equal to 100000 (e.g. importing 100000 rows). You need to mention a HDFS location which will be used as a destination directory for the imported data (--target-dir parameter). Remember one thing here is that the target directory should not be existing prior to run import command otherwise Sqoop will throw an error. The last parameter -m represents the number of map tasks to run in parallel for the entire import job.

Once you have your option file ready, you can execute the Sqoop import command as:

sqoop import --options-file option.par

Using option file is not mandatory, I'm just using it for my convenience. You can also pass each of the parameter from your console and execute the import job. Example:

Export from Hive to Oracle:

For export, I will be using some of the parameters which I used during import as they are common for both import and export job. Assume I processed(by MR jobs) the data generated by import job and inserted them into Hive tables. Now I want to export those Hive tables to Oracle. If you are familiar with Hive, you may know that Hive moves/copies data to its warehouse folder by default. I'm using Hortonworks's distribution and for my case Hive'e warehouse folder is located at: "/apps/hive/warehouse/emp_record". Here, emp_record is one of the Hive table I want to export from.

I have already created a matching table "Emp_Record" in my Oracle inside the same schema "Employee_Reporting". To export the Hive table, I'm executing the following command:

Notice that instead of using --target-dir, I'm using --export-dir, this is the location of the Hive table's warehouse folder and data will be exporting from there.

Now assume, inside the warehouse directory, I have a file 00000_1 (which contains the data of Hive table Emp_Record) and some of its lines are:

As you can see, each of columns/fields are tab delimited and each of the rows are separated by a new line. Again we see here that there is an entire row which contains null as their values (Ideally you might not have null values as you might want to filter those values from your M-R jobs). But say we have all kind of values, so we need to tell Sqoop how to treat each of those values. Because of that, I'm using --input-fields-terminated-by parameter to inform that the fields are tab delimited and --input-lines-terminated-by parameter to distinguish rows. Again from Sqoop side, there are two kinds of column - string column and non-string column. Sqoop needs to know what string value is interpreting a null value. Because of that I'm using --input-null-string and --input-null-non-string parameters for two column types and passing '\\N' as their value because for my case '\\N' is null.

Wrapping Up:

Sometimes you will face some issues during export when your Oracle table has a very tight constraint (e.g. not null, time-stamp, expecting value in specific format, etc). In that case, the best idea is to export the Hive table/HDFS data to a temporary Oracle table without any modification to make Sqoop happy :). And then write a SQL script to convert and filter those data to your expected values and load them into your main Oracle table.

The above two examples are just showing a very basic import and export Sqoop job. There are a lot of setting in Sqoop you can use. Once you are able to run export/import job successfully, I would recommend you to try the same job with different parameters and see how it goes. You can find all available options in the Sqoop user guide.

Note: For privacy purpose, I had to modify several lines on this post from my original post. So if you find something is not working or facing any issues, please do not hesitate to contact me.