Sqoop - Eval

Eval is normally used to run simple sql queries against the database server.It will also preview the result on the console level.Eval can be used to evaluate any type of query like DDL/DML.

EVAL is only to check the database connection and also to preview the small set of data.It will provide the user to test the simple queries.

Sqoop Syntax :-

sqoop --eval {generic-args} {eval args}

Generic args :-

Argument	Description
–connect <jdbc-uri>	Specify JDBC connect string
–connection-manager <class-name>	Specify connection manager class to use
–driver <class-name>	Manually specify JDBC driver class to use
–hadoop-mapred-home <dir>	Override $HADOOP_MAPRED_HOME
–help	Print usage instructions
–password-file	Set path for a file containing the authentication password
-P	Read password from console
–password <password>	Set authentication password
–username <username>	Set authentication username
–verbose	Print more information while working
–connection-param-file <filename>	Optional properties file that provides connection parameters
–relaxed-isolation	Set connection transaction isolation to read uncommitted for the mappers.

Eval Args :-

e ,query Execute statement in SQL.

query examples :-

sqoop eval \
–connect jdbc:mysql://localhost/test \
–username root \
–query “SELECT * FROM sqoop_test ”

Hive - Reading JSON using Serde

Reading JSON in Hive is quite trickier but JSON serde has made our life easier.The JSON serde can be downloaded from any third party website.The JSON serde for JSON file is available in Hive 0.12 and later version.

We can download JSON serde from any of the sites like :-

https://code.google.com/archive/p/hive-json-serde/downloads

We have downloaded a sample JSON file  from https://support.oneskyapp.com/hc/en-us/articles/208047697-JSON-sample-files


Step 1.) Download the Serde from the above link and store it in any of the required folder .



Step 2.) Once the JSON serde has been downloaded , kindly add it to the Hive using below command.

ADD path/to/jar Jarfile.


Step 3.) Create the required table format using the below syntax .

create external table serde_fruit(fruit string,size string,color string) ROW FORMAT SERDE 'org.apache.hadoop.hive.contrib.serde2.JsonSerde' location ‘/serde_ex’;



Step 4. ) validate the data by using the select query.