I have the .sql files in HDFS which has mysql INSERT queries. I created an external table in impala with the appropriate schema. Now I want to run all the insert commands stored in HDFS to the table. Is there a way to do it? Data size is 900GB!
Is any other way to import the .sql files from HDFS? We have tried with hive but it requires all the insert fields to be in lowercase which we do not have.
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I have a csv file named test.csv on my HDFS.
I have created an Avro table (avro_test) using Hue with the same column names as the csv file. I want to use a sqoop command to put the csv elements in the Avro table.
What sqoop command will achieve this?
Sqoop is meant to load/transfer data between RDBMS and Hadoop. You can just insert the CSV data into the avro table you have created.
Please refer below link.
Load from CSV File to Hive Table with Sqoop?
I dont have write permission on hdfs cluster.
I am accessing database tables created/stored on hdfs using hive via edge node.
I have read access.
I want to export data from tables located on hdfs into csv on my local system.
How should i do it?
insert overwrite local directory '/____/____/' row format delimited fields terminated by ',' select * from table;
Note that this may create multiple files and you may want to concatenate them on the client side after it's done exporting.
I'm loading data from HDFS to mySQL using SQOOP, in this data one record has got more than 70 fields, making it difficult to define the schema while creating the table in RDBMS.
Is there a way to use AVRO tables to dynamically create the table with schema in RDBMS using SQOOP?
Or is there any some tool which does the same?
This is not supported in sqoop today. From the sqoop documentation
The export tool exports a set of files from HDFS back to an RDBMS. The
target table must already exist in the database. The input files are
read and parsed into a set of records according to the user-specified
delimiters.
I am now preparing to store data in .csv files into hive. Of course, because of the good performance of parquet file format, the hive table should is parquet format. So, the normal way, is to create a temp table whose format is textfile, then I load local CSV file data into this temp table, and finally, create a same-structure parquet table and use sql insert into parquet_table values (select * from textfile_table);.
But I don't think this temp textfile table is necessary. So, my question is, is there a way for me to load these local .csv files into hive parquet-format table directly, namely, not to resort the a temp table? Or a easier way to accomplish this task?
As stated in Hive documentation:
NO verification of data against the schema is performed by the load command.
If the file is in hdfs, it is moved into the Hive-controlled file system namespace.
You could skip a step by using CREATE TABLE AS SELECT for the parquet table.
So you'll have 3 steps:
Create text table defining the schema
Load data into text table (move the file into the new table)
CREATE TABLE parquet_table AS SELECT * FROM textfile_table STORED AS PARQUET; supported from hive 0.13
I have a csv in my local directory and i wish to create a hive table of it..The problem is csv has many columns...
In authors words Sqoop means Sql-to-Hadoop.. you can't use Sqoop to import data from your local to hdfs in any way.
Sqoop (“SQL-to-Hadoop”) is a straightforward command-line tool with the following capabilities:
Imports individual tables or entire databases to files in HDFS
Generates Java classes to allow you to interact with your imported data
Provides the ability to import from SQL databases straight into your Hive data warehouse
For more information follow below links:
http://blog.cloudera.com/blog/2009/06/introducing-sqoop/
http://kickstarthadoop.blogspot.com/2011/06/how-to-speed-up-your-hive-queries-in.html