I am exporting a Hive partitioned table to Teradata. How can the partitioned column be included in the export?
I know this can be done by copying the data to HDFS directory and then using that directory as source for sqoop export. Is there an one step approach to include the partitioned column during export?
Related
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?
All,
I have question for sqooping , I am sqooping around 2tb of data for one table and then need to write ORC table wit h that . What's best way to achieve
1) sqoop all data in dir1 as text and write HQL to load into ORC table , where script fail for vertex issue
2) sqoop data in chucks and process and append into hive table ( have you done this ? )
3) sqoop hive import to write all data to hive ORC table
Which is best way ?
Option three will be better because you dont need to create a hive table and again loading data into it and storing that data in orc format it is a long process for 2tb of data so its better to give in sqoop so it can directly push the data into hive table with orc format but when you are returning data from hive table to rdbms you have to use sqoopserde
After insertion of orc files into the folder of a table with hdfs copy, how to update that hive table's data to see those data when querying with hive.
Best Regards.
If the table is not partitioned then once the files are in HDFS in the folder that is specified in the LOCATION clause, then the data should be available for querying.
If the table is partitioned then u first need to run an ADD PARTITION statement.
As mentioned in upper answer by belostoky. if the table is not partitioned then you can directly query your table with the updated data
But in case if you table is partitioned you need to add partitions first in hive table that you can do using
You can use alter table statement to add partitions like shown below
ALTER TABLE table1
ADD PARTITION (dt='<date>')
location '<hdfs file path>'
once partitions are added hive metastore should be aware of changes so you need to run
msck repair table table1
to add partitions in metastore.
Once done you can query your data
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 1 TB data in my HDFS in .csv format. When I load it in my Hive table what will be the total size of data. I mean will there be 2 copies of same data i.e 1 Copy in HDFS and other in Hive table ? Plz clarify. Thanks in advance.
If you create a hive external table, you provide a HDFS location for the table and you store that data into that particular location.
When you create a hive internal table hive create a directory into /apps/hive/warehouse/ directory.
Say, your table name is table1 then your directory will be /apps/hive/warehouse/table1
This directory is also a HDFS directory and when you load data into the table into internal table it goes into its directory.
Hive creates a mapping between table and their corresponding HDFS location and hence when you read the data its reading from the corresponding mapped directory.
Hence there wont be duplicate copy of data corresponding to table and their HDFS location.
But if in your Hadoop cluster Data Replication factor is set to 3(default replication) then it will take 3TB cluster disk space(as you have 1TB data) but there wont be any effect of your hive table data.
Please see below link to know more about Data replication.
http://hadoop.apache.org/docs/r1.2.1/hdfs_design.html#Data+Replication
It depends whether you are creating an internal or external table in Hive.
If you create an external table in Hive, it will create a mapping on where your data is stored in HDFS and there won't be any duplication at all. Hive will automatically pick the data where ever it is stored in HDFS.
Read more about external tables here: https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DDL#LanguageManualDDL-ExternalTables