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;
Related
When load data from HDFS to Hive, using
LOAD DATA INPATH 'hdfs_file' INTO TABLE tablename;
command, it looks like it is moving the hdfs_file to hive/warehouse dir.
Is it possible (How?) to copy it instead of moving it, in order, for the file, to be used by another process.
from your question I assume that you already have your data in hdfs.
So you don't need to LOAD DATA, which moves the files to the default hive location /user/hive/warehouse. You can simply define the table using the externalkeyword, which leaves the files in place, but creates the table definition in the hive metastore. See here:
Create Table DDL
eg.:
create external table table_name (
id int,
myfields string
)
location '/my/location/in/hdfs';
Please note that the format you use might differ from the default (as mentioned by JigneshRawal in the comments). You can use your own delimiter, for example when using Sqoop:
row format delimited fields terminated by ','
I found that, when you use EXTERNAL TABLE and LOCATION together, Hive creates table and initially no data will present (assuming your data location is different from the Hive 'LOCATION').
When you use 'LOAD DATA INPATH' command, the data get MOVED (instead of copy) from data location to location that you specified while creating Hive table.
If location is not given when you create Hive table, it uses internal Hive warehouse location and data will get moved from your source data location to internal Hive data warehouse location (i.e. /user/hive/warehouse/).
An alternative to 'LOAD DATA' is available in which the data will not be moved from your existing source location to hive data warehouse location.
You can use ALTER TABLE command with 'LOCATION' option. Here is below required command
ALTER TABLE table_name ADD PARTITION (date_col='2017-02-07') LOCATION 'hdfs/path/to/location/'
The only condition here is, the location should be a directory instead of file.
Hope this will solve the problem.
Maybe this is an easy question but, I am having a difficult time resolving the issue. At this time, I have an pseudo-distributed HDFS that contains recordings that are encoded using protobuf 3.0.0. Then, using Elephant-Bird/Hive I am able to put that data into Hive tables to query. The problem that I am having is partitioning the data.
This is the table create statement that I am using
CREATE EXTERNAL TABLE IF NOT EXISTS test_messages
PARTITIONED BY (dt string)
ROW FORMAT SERDE
"com.twitter.elephantbird.hive.serde.ProtobufDeserializer"
WITH serdeproperties (
"serialization.class"="path.to.my.java.class.ProtoClass")
STORED AS SEQUENCEFILE;
The table is created and I do not receive any runtime errors when I query the table.
When I attempt to load data as follows:
ALTER TABLE test_messages_20180116_20180116 ADD PARTITION (dt = '20171117') LOCATION '/test/20171117'
I receive an "OK" statement. However, when I query the table:
select * from test_messages limit 1;
I receive the following error:
Failed with exception java.io.IOException:java.lang.IllegalArgumentException: FieldDescriptor does not match message type.
I have been reading up on Hive table and have seen that the partition columns do not need to be part of the data being loaded. The reason I am trying to partition the date is both for performance but, more so, because the "LOAD DATA ... " statements move the files between directories in HDFS.
P.S. I have proven that I am able to run queries against hive table without partitioning.
Any thoughts ?
I see that you have created EXTERNAL TABLE. So you cannot add or drop partition using hive. you need to create a folder using hdfs or MR or SPARK. EXTERNAL table can only be read by hive but not managed by HDFS. You can check the hdfs location '/test/dt=20171117' and you will see that folder has not been created.
My suggestion is create the folder(partition) using "hadoop fs -mkdir '/test/20171117'" then try to query the table. although it will give 0 row. but you can add the data to that folder and read from Hive.
You need to specify a LOCATION for an EXTERNAL TABLE
CREATE EXTERNAL TABLE
...
LOCATION '/test';
Then, is the data actually a sequence file? All you've said is that it's protobuf data. I'm not sure how the elephantbird library works, but you'll want to double check that.
Then, your table locations need to look like /test/dt=value in order for Hive to read them.
After you create an external table over HDFS location, you must run MSCK REPAIR TABLE table_name for the partitions to be added to the Hive metastore
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 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).
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.