whats the importance of $CONDITIONS in every sqoop import query ?
ex:
select col1, col2 from test_table where \$CONDITIONS
What if I need to put my own where condition in the query and it works ?
The significance is explained in the Sqoop User Guide and in Apache Sqoop cookbook. To put it into nutshell, Sqoop needs a placeholder in the query to populate it with generated slices to enable parallel import.
It will act as a place holder where sqoop replaces it to make the query works parallel. It is must to put $CONDTIONS when you are importing query results. Still you can place your condition as below,
Select col1,col2 from table where $CONDITIONS and "your condtion"
Note: you can directly see in stack trace what the condition sqoop places here at $CONDITIONS. Eg. The first thing you can see is the condition "where 1=0" to fetch the metadata or schema from source table.
Related
Is there any tools available?
Normally I check by doing manual checks like count(*), min , max , doing select where query in both rdbms and hive table. Is there any other way?
Please use --validate in sqoop import or export to get row count between source and destination.
Update: Column Level checking.
There is no in built parameter in sqoop to achieve this.But you can do this as below:
1.Store the data imported in a temp table.
Use shell script for below:
2.Get the data from source table and compare it with temp table using shell variables.
3.If it matches,then copy the data from temp to original table
I am trying to move records with null values in a particular column to a particular table and non-null records to another while SQOOP import. tried to explore on goolge but there is not much beyond --null-string and --null-non-String params but that will just replace with the defined characters ...
I can think of following ways to handle it
once importing into hive, run a dedup to filter out the records but this is something to be tried in worst case.
handling at sqoop level itself(no clue on this)
could any expert here can help me with the above ask.
ENV details : its a plain Apache hadoop cluster. sqoop version 1.4.6
We can try making use of --query option along with the sqoop-import command
--query select * from table where column is null and $CONDITIONS
And in a similar way for not null condition also.
There will be 2 sqoop import jobs here.
I have some very large tables that I am trying to sqoop from a Source System Data Warehouse into HDFS, but limited bandwidth to do so. I would like to only pull the columns I need, and minimize the run-time for getting the tables stood up.
The sqoop currently pulls something like this:
SELECT
ColumnA,
ColumnB,
....
ColumnN
FROM
TABLE_A
LEFT JOIN
TABLE_B
ON
...
LEFT JOIN
TABLE_N
....
Is It possible to perform an incremental sqoop, given that the data is stored in a star-schema format, and the dimensions could update independently of the facts?
Or, is the only solution to sqoop the entire table, for the columns that I need, incrementally, and perform the joins on the HDFS side?
For incremental imports you need to use --incremental flag. Please refer to below link for more info :-
https://sqoop.apache.org/docs/1.4.2/SqoopUserGuide.html#_incremental_imports
you need to specify —incremental to tell sqoop that you want an incremental load —check-column to specify which column is used for incremental sqooping and —last-value to say from which value you want to start sqooping the next load.
This is just half the picture. There are more ways to do this.for eg. you can use —query option and your query would be like Select * from table where column > 123. This is basically the same thing. You would need to record the last/max value for the selected column and use it for next import.
What is the significance of $conditions clause in sqoop import command?
select col1, col2 from test_table where \$CONDITIONS
Sqoop performs highly efficient data transfers by inheriting Hadoop’s parallelism.
To help Sqoop split your query into multiple chunks that can be
transferred in parallel, you
need to include the $CONDITIONS placeholder in the where clause of your query.
Sqoop
will automatically substitute this placeholder with the generated conditions specifying
which slice of data should be transferred by each individual task.
While you could skip
$CONDITIONS by forcing Sqoop to run only one job using the --num-mappers 1 param‐
eter, such a limitation would have a severe performance impact.
For example:-
If you run a parallel import, the map tasks will execute your query
with different values substituted in for $CONDITIONS. one mapper
may execute "select bla from foo WHERE (id >=0 AND id < 10000)", and
the next mapper may execute "select bla from foo WHERE (id >= 10000
AND id < 20000)" and so on.
I am looking at some existing code written in sqoop. I can see queries like
select * from table where $CONDITIONS
This code works and sqoop is pulling data only for a specific date range.
This is good, but how does sqoop know which column in the table it has to apply the date range filter (if the table in question has multiple date time columns).