I am Trying to load data into hive from HDFS . But I Observed that data is moving , meaning after loading the data into hive environment if i look at the HDFS the data which i have loaded is not present . can You Please answer this question with example .
If you would like to create a table in Hive from data in HDFS without moving the data into /user/hive/warehouse/, you should use the optional EXTERNAL and LOCATION keywords. For example, from this page, we have the following example CREATE TABLE statement:
hive> CREATE EXTERNAL TABLE userline(line STRING) ROW FORMAT
DELIMITED FIELDS TERMINATED BY ','
LINES TERMINATED BY '\n'
STORED AS TEXTFILE
LOCATION '/home/admin/userdata';
Without those, Hive will take your data from HDFS and load it into /user/hive/warehouse (and if the table is dropped, the data is also deleted).
Related
i have data set having 100+ columns for each row. question is how can i load selected columns using hive into hdfs.
for example : col1 ,col2,col3...col50,col51....col99,col100 . I need to load only selected columns col1,col2,col34 and col99.
Approach 1:
1. load all the columns
2. and create view based on selected columns.
Approach 1 - cons- i need to load all the columns unnecessary and it will consume more memory in hdfs also i need to write big query for specifying the column
. Any other best approach.
Hive provides a tabular view on top of HDFS data. If your data is in HDFS, then you can create an external table on it to reference the existing data. You will need to put a schema over the data. This is a one time effort and then you can use all the features of Hive to explore and analyze the dataset. Hive supports views also.
Illustration
Sample data file: data.csv
1,col_1a,col1b
2,col_2a,col2b
3,col_3a,col3b
4,col_4a,col4b
5,col_5a,col5b
6,col_6a,col6b
7,col_7a,col7b
Load and verify data in HDFS
hadoop fs -mkdir /hive-data/mydata
hadoop fs -put data.csv /hive-data/mydata
hadoop fs -cat /hive-data/mydata/*
1,col_1a,col1b
2,col_2a,col2b
3,col_3a,col3b
4,col_4a,col4b
5,col_5a,col5b
6,col_6a,col6b
7,col_7a,col7b
Create a Hive table on top of the HDFS data in default database
CREATE EXTERNAL TABLE default.mydata
(
id int,
data_col1 string,
data_col2 string
)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
LINES TERMINATED BY '\n'
LOCATION 'hdfs:///hive-data/mydata';
Query the Hive table
select * from default.mydata;
mydata.id mydata.data_col1 mydata.data_col2
1 col_1a col1b
2 col_2a col2b
3 col_3a col3b
4 col_4a col4b
5 col_5a col5b
6 col_6a col6b
7 col_7a col7b
I completed my hadoop course now I want to work on Hadoop. I want to know the workflow from data ingestion to visualize the data.
I am aware of how eco system components work and I have built hadoop cluster with 8 datanodes and 1 namenode:
1 namenode --Resourcemanager,Namenode,secondarynamenode,hive
8 datanodes--datanode,Nodemanager
I want to know the following things:
I got data .tar structured files and first 4 lines have got description.how to process this type of data im little bit confused.
1.a Can I directly process the data as these are tar files.if its yes how to remove the data in the first four lines should I need to untar and remove the first 4 lines
1.b and I want to process this data using hive.
Please suggest me how to do that.
Thanks in advance.
Can I directly process the data as these are tar files.
Yes, see the below solution.
if yes, how to remove the data in the first four lines
Starting Hive v0.13.0, There is a table property, tblproperties ("skip.header.line.count"="1") while creating a table to tell Hive the number of rows to ignore. To ignore first four lines - tblproperties ("skip.header.line.count"="4")
CREATE TABLE raw (line STRING)
ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t' LINES TERMINATED BY '\n';
CREATE TABLE raw_sequence (line STRING)
STORED AS SEQUENCEFILE
tblproperties("skip.header.line.count"="4");
LOAD DATA LOCAL INPATH '/tmp/test.tar' INTO TABLE raw;
SET hive.exec.compress.output=true;
SET io.seqfile.compression.type=BLOCK; -- NONE/RECORD/BLOCK (see below)
INSERT OVERWRITE TABLE raw_sequence SELECT * FROM raw;
To view the data:
select * from raw_sequence
Reference: Compressed Data Storage
Follow the below steps to achieve your goal:
Copy the data(ie.tar file) to the client system where hadoop is installed.
Untar the file and manually remove the description and save it in local.
Create the metadata(i.e table) in hive based on the description.
Eg: If the description contains emp_id,emp_no,etc.,then create table in hive using this information and also make note of field separator used in the data file and use the corresponding field separator in create table query. Assumed that file contains two columns which is separated by comma then below is the syntax to create the table in hive.
Create table tablename (emp_id int, emp_no int)
Row Format Delimited
Fields Terminated by ','
Since, data is in structured format, you can load the data into hive table using the below command.
LOAD DATA LOCAL INPATH '/LOCALFILEPATH' INTO TABLE TABLENAME.
Now, local data will be moved to hdfs and loaded into hive table.
Finally, you can query the hive table using SELECT * FROM TABLENAME;
I have created an external table in Hive using following:
create external table hpd_txt(
WbanNum INT,
YearMonthDay INT ,
Time INT,
HourlyPrecip INT)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
LINES TERMINATED BY '\n'
stored as textfile
location 'hdfs://localhost:9000/user/hive/external';
Now this table is created in location */hive/external.
Step-1: I loaded data in this table using:
load data inpath '/input/hpd.txt' into table hpd_txt;
the data is successfully loaded in the specified path ( */external/hpd_txt)
Step-2: I delete the table from */hive/external path using following:
hadoop fs -rmr /user/hive/external/hpd_txt
Questions:
why is the table deleted from original path? (*/input/hpd.txt is deleted from hdfs but table is created in */external path)
After I delete the table from HDFS as in step 2, and again I use show tables; It still gives the table hpd_txt in the external path.
so where is this coming from.
Thanks in advance.
Hive doesn't know that you deleted the files. Hive still expects to find the files in the location you specified. You can do whatever you want in HDFS and this doesn't get communicated to hive. You have to tell hive if things change.
hadoop fs -rmr /user/hive/external/hpd_txt
For instance the above command doesn't delete the table it just removes the file. The table still exists in hive metastore. If you want to delete the table then use:
drop if exists tablename;
Since you created the table as an external table this will drop the table from hive. The files will remain if you haven't removed them. If you want to delete an external table and the files the table is reading from you can do one of the following:
Drop the table and then remove the files
Change the table to managed and drop the table
Finally the location of the metastore for hive is by default located here /usr/hive/warehouse.
The EXTERNAL keyword lets you create a table and provide a LOCATION so that Hive does not use a default location for this table. This comes is handy if you already have data generated. Else, you will have data loaded (conventionally or by creating a file in the directory being pointed by the hive table)
When dropping an EXTERNAL table, data in the table is NOT deleted from the file system.
An EXTERNAL table points to any HDFS location for its storage, rather than being stored in a folder specified by the configuration property hive.metastore.warehouse.dir.
Source: Hive docs
So, in your step 2, removing the file /user/hive/external/hpd_txt removes the data source(data pointing to the table) but the table still exists and would continue to point to hdfs://localhost:9000/user/hive/external as it was created
#Anoop : Not sure if this answers your question. let me know if you have any questions further.
Do not use load path command. The Load operation is used to MOVE ( not COPY) the data into corresponding Hive table. Use put Or copyFromLocal to copy file from non HDFS format to HDFS format. Just provide HDFS file location in create table after execution of put command.
Deleting a table does not remove HDFS file from disk. That is the advantage of external table. Hive tables just stores metadata to access data files. Hive tables store actual data of data file in HIVE tables. If you drop the table, the data file is untouched in HDFS file location. But in case of internal tables, both metadata and data will be removed if you drop table.
After going through you helping comments and other posts, I have found answer to my question.
If I use LOAD INPATH command then it "moves" the source file to the location where external table is being created. Which although, wont be affected in case of dropping the table, but changing the location is not good. So use local inpath in case of loading data in Internal tables .
To load data in external tables from a file located in the HDFS, use the location in the CREATE table query which will point to the source file, for example:
create external table hpd(WbanNum string,
YearMonthDay string ,
Time string,
hourprecip string)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
LINES TERMINATED BY '\n'
stored as textfile
location 'hdfs://localhost:9000/input/hpd/';
So this sample location will point to the data already present in HDFS in this path. so no need to use LOAD INPATH command here.
Its a good practice to store a source files in their private dedicated directories. So that there is no ambiguity while external tables are created as data is in a properly managed directory system.
Thanks a lot for helping me understand this concept guys! Cheers!
I have to create a hive table from data present in oracle tables.
I'm doing a sqoop, thereby converting the oracle data into HDFS files. Then I'm creating a hive table on the HDFS files.
The sqoop completes successfully and the files also get generated in the HDFS target directory.
Then I run the create table script in hive. The tables gets created. But it is an empty table, no data is seen in the hive table.
Has anyone faced a similar problem?
Hive default delimiter is ctrlA, if you don't specify any delimiter it will take default delimiter. Add below line in your hive script .
row format delimited fields terminated by '\t'
Your Hive script and your expectation is wrong. You are trying to create a partitioned table on the data that you have already imported, partitions won't work that way. If your query has no partition in it then you can able to see data.
Basically If you want partitioned table , you can't create on the under lying data like you have tried above. If you want hive partition load the data from intermediate table or that sqoop directory to your partitioned table to get Hive partitions.
I have log files stored as text in HDFS. When I load the log files into a Hive table, all the files are copied.
Can I avoid having all my text data stored twice?
EDIT: I load it via the following command
LOAD DATA INPATH '/user/logs/mylogfile' INTO TABLE `sandbox.test` PARTITION (day='20130221')
Then, I can find the exact same file in:
/user/hive/warehouse/sandbox.db/test/day=20130220
I assumed it was copied.
use an external table:
CREATE EXTERNAL TABLE sandbox.test(id BIGINT, name STRING) ROW FORMAT
DELIMITED FIELDS TERMINATED BY ','
LINES TERMINATED BY '\n'
STORED AS TEXTFILE
LOCATION '/user/logs/';
if you want to use partitioning with an external table, you will be responsible for managing the partition directories.
the location specified must be an hdfs directory..
If you drop an external table hive WILL NOT delete the source data.
If you want to manage your raw files, use external tables. If you want hive to do it, the let hive store inside of its warehouse path.
I can say, instead of copying data by your java application directly to HDFS, have those file in local file system, and import them into HDFS via hive using following command.
LOAD DATA LOCAL INPATH '/your/local/filesystem/file.csv' INTO TABLE `sandbox.test` PARTITION (day='20130221')
Notice the LOCAL
You can use alter table partition statement to avoid data duplication.
create External table if not exists TestTable (testcol string) PARTITIONED BY (year INT,month INT,day INT) row format delimited fields terminated by ',';
ALTER table TestTable partition (year='2014',month='2',day='17') location 'hdfs://localhost:8020/data/2014/2/17/';
Hive (atleast when running in true cluster mode) can not refer to external files in local file system. Hive can automatically import the files during table creation or load operation. The reason behind this can be that Hive runs MapReduce jobs internally to extract the data. MapReduce reads from the HDFS as well as writes back to HDFS and even runs in distributed mode. So if the file is stored in local file system, it can not be used by the distributed infrastructure.