How to point one Hive Table to Multiple External Files? - hadoop

I would like to be able to append multiple HDFS files to one Hive table while leaving the HDFS files in their original directory. These files are created are located in different directories.
The LOAD DATA INPATH moves the HDFS file to the hive warehouse directory.
As far as I can tell, an External Table must be pointed to one file, or to one directory within which multiple files with the same schema can be placed. However, my files would not be underneath a single directory.
Is it possible to point a single Hive table to multiple external files in separate directories, or to otherwise copy multiple files into a single hive table without moving the files from their original HDFS location?
Expanded Solution off of Pradeep's answer:
For example, my files look like this:
/root_directory/<job_id>/input/<dt>
Pretend the schema of each is (foo STRING, bar STRING, job_id STRING, dt STRING)
I first create an external table. However, note that my DDL does not contain an initial location, and it does not include the job_id and dt fields:
CREATE EXTERNAL TABLE hivetest (
foo STRING,
bar STRING
) PARTITIONED BY (job_id STRING, dt STRING)
ROW FORMAT DELIMITED FIELDS TERMINATED BY ','
;
Let's say I have two files I wish to insert located at:
/root_directory/b1/input/2014-01-01
/root_directory/b2/input/2014-01-02
I can load these two external files into the same Hive table like so:
ALTER TABLE hivetest
ADD PARTITION(job_id = 'b1', dt='2014-01-01')
LOCATION '/root_directory/b1/input/2014-01-01';
ALTER TABLE hivetest
ADD PARTITION(job_id = 'b2', dt='2014-01-02')
LOCATION '/root_directory/b2/input/2014-01-02';
If anyone happens to require the use of Talend to perform this, they can use the tHiveLoad component like so [edit: This doesn't work; check below]:
The code talend produces for this using tHiveLoad is actually LOAD DATA INPATH ..., which will remove the file off its original location in HDFS.
You will have to do the earlier ALTER TABLE syntax in a tHiveLoad instead.

The short answer is yes. A Hive External Table can be pointed to multiple files/directories. The long answer will depend on the directory structure of your data. The typical way you do this is to create a partitioned table with the partition columns mapping to some part of your directory path.
E.g. We have a use case where an external table points to thousands of directories on HDFS. Our paths conform to this pattern /prod/${customer-id}/${date}/. In each of these directories we have approx 100 files. In mapping this into a Hive Table, we created two partition columns, customer_id and date. So every day, we're able to load the data into Hive, by doing
ALTER TABLE x ADD PARTITION (customer_id = "blah", dt = "blah_date") LOCATION '/prod/blah/blah_date';

Try this:
LOAD DATA LOCAL INPATH '/path/local/file_1' INTO TABLE tablename;
LOAD DATA LOCAL INPATH '/path/local/file_2' INTO TABLE tablename;

Related

data deleted from hdfs after using hive load command [duplicate]

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.

Where is HIVE metadata stored by default?

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!

How to add partition using hive by a specific date?

I'm using hive (with external tables) to process data stored on amazon S3.
My data is partitioned as follows:
DIR s3://test.com/2014-03-01/
DIR s3://test.com/2014-03-02/
DIR s3://test.com/2014-03-03/
DIR s3://test.com/2014-03-04/
DIR s3://test.com/2014-03-05/
s3://test.com/2014-03-05/ip-foo-request-2014-03-05_04-20_00-49.log
s3://test.com/2014-03-05/ip-foo-request-2014-03-05_06-26_19-56.log
s3://test.com/2014-03-05/ip-foo-request-2014-03-05_15-20_12-53.log
s3://test.com/2014-03-05/ip-foo-request-2014-03-05_22-54_27-19.log
How to create a partition table using hive?
CREATE EXTERNAL TABLE test (
foo string,
time string,
bar string
) PARTITIONED BY (? string)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\t'
LOCATION 's3://test.com/';
Could somebody answer this question ? Thanks!
First start with the right table definition. In your case I'll just use what you wrote:
CREATE EXTERNAL TABLE test (
foo string,
time string,
bar string
) PARTITIONED BY (dt string)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\t'
LOCATION 's3://test.com/';
Hive by default expects partitions to be in subdirectories named via the convention s3://test.com/partitionkey=partitionvalue. For example
s3://test.com/dt=2014-03-05
If you follow this convention you can use MSCK to add all partitions.
If you can't or don't want to use this naming convention, you will need to add all partitions as in:
ALTER TABLE test
ADD PARTITION (dt='2014-03-05')
location 's3://test.com/2014-03-05'
If you have existing directory structure that doesn't comply <partition name>=<partition value>, you have to add partitions manually. MSCK REPAIR TABLE won't work unless you structure your directory like so.
After you specify location on table creation like:
CREATE EXTERNAL TABLE test (
foo string,
time string,
bar string
)
PARTITIONED BY (dt string)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\t'
LOCATION 's3://test.com/';
You can add partition without specifying full path:
ALTER TABLE test ADD PARTITION (dt='2014-03-05') LOCATION '2014-03-05';
Although I've never checked it, I suggest you to move your partitions into a folder inside the bucket, not directly in the bucket itself. E.g. from s3://test.com/ to s3://test.com/data/.
If you are going to partition using date field you need s3 folder structure as mentioned below:
s3://test.com/date=2014-03-05/ip-foo-request-2014-03-05_04-20_00-49.log
In such case you can create external table with partition column as date
and run MSCK REPAIR TABLE EXTERNAL_TABLE_NAME to update hive meta store.
Please look at the response posted above by Carter Shanklin. You need to make sure your files are stored in the directory structure as partitionkey=partitionvalue i.e. Hive by default expects partitions to be in subdirectories named via the convention.
In your example it should be stored as
s3://test.com/date=20140305/ip-foo-request-2014-03-05_04-20_00-49.log.
Steps to be followed:
i) Make sure data exists in the above structure
ii) Create the external table
iii) Now run the msck repair table.
I think the the data is present in the s3 location and might not updated in the metadata, (emrfs). In order this to work first do emrfs import and emrfs sync.
And then apply the msck repair.
It will add all the partitions that are present in s3

Is it possible to have multiple hive tables represented within the same HDFS directory structure?

Is it possible to have multiple hive tables represented within the same HDFS directory structure? In other words, is there a way to have multiple hive tables pointing to same/overlapping HDFS paths?
Here is my situation:
I have a table named "mytable", located in hdfs:/tables/mytable
CREATE EXTERNAL TABLE mytable
(
id int,
...
[a whole bunch of columns]
...
PARTITIONED BY (logname STRING)
STORED AS [I-do-not-know-what-just-yet]
LOCATION 'hdfs:/tables/mytable';
So, HDFS will look like:
hdfs:/tables/mytable/logname=tarzan/....
hdfs:/tables/mytable/logname=jane/....
hdfs:/tables/mytable/logname=whoa/....
Is it possible to have a hive table, named "tarzan", located in hdfs:/tables/mytable/logname=tarzan ? Same with hive table "jane", located in hdfs:/tables/mytable/logname=jane, etc.
The tarzan, jane, whoa, etc sub-tables share some columns (timestamp, ip_address, country, user_id, and some others), but there will also be a lot of columns that they do not have in common.
Is there a way to store this data once in HDFS, and use it for multiple tables as I described above? Furthermore, is there a way to store the data in an efficient way, since many of the tables will have columns that are not in common? Would a file format like RCFILE or PARQUET work in this case?
Thanks so much for any hints or help anyone can provide,
Yes, we can have multiple hive tables with the same underlying HDFS directory.
Example:
Create table emp and load data file file3 into it.
create table emp (id int, name string, salary int)
row format delimited
fields terminated by ','
-- default location would be used
load data
local inpath '/home/parv/testfiles/file3'
into table emp;
Create another table mirror. When you will select data from mirror table, it would be as same as of emp table (contents of file3).
create table mirror (id int, name string, salary int)
row format delimited
fields terminated by ','
location 'hdfs:///user/hive/warehouse/parv.db/base';
Load data into mirror table. When you will select data either from mirror table or emp table, it would return same results (contents of file3 and file4).
load data
local inpath '/home/parv/testfiles/file4'
into table mirror;
Conclusion:
Same data files are shared among both tables emp and mirror.
But, strange, the HDFS filesystem only shows data directory for emp table and not for mirror table. However, both the tables are present in hive and so can be queried.
Answering my own question:
It IS possible to have multiple hive tables represented by the same HDFS directory structure, but for what I am looking to do:
A mytable table partitioned by logname (logname=tarzan, logname=jane, etc...)
A separate table for each logname: A "tarzan" table with only columns used by the tarzan table, and not any other logname, same for the "jane" table, etc
Only represent the data one time in HDFS
A better solution is to have the 1 mytable table, partitioned by logname, AND create views for each logname table, with only the subset of columns needed in each.
Yes, you could point multiple tables to the same location on HDFS. However, Hive doesn't support dynamic columns.
Is there a reason you can't just have 3 different tables? This would allow you do have different schemas (columns) for each.
--Brandon

Hive loading in partitioned table

I have a log file in HDFS, values are delimited by comma. For example:
2012-10-11 12:00,opened_browser,userid111,deviceid222
Now I want to load this file to Hive table which has columns "timestamp","action" and partitioned by "userid","deviceid". How can I ask Hive to take that last 2 columns in log file as partition for table? All examples e.g. "hive> LOAD DATA INPATH '/user/myname/kv2.txt' OVERWRITE INTO TABLE invites PARTITION (ds='2008-08-15');" require definition of partitions in the script, but I want partitions to set up automatically from HDFS file.
The one solution is to create intermediate non-partitioned table with all that 4 columns, populate it from file and then make an INSERT into first_table PARTITION (userid,deviceid) select from intermediate_table timestamp,action,userid,deviceid; but that is and additional task and we will have 2 very similiar tables.. Or we should create external table as intermediate.
Ning Zhang has a great response on the topic at http://grokbase.com/t/hive/user/114frbfg0y/can-i-use-hive-dynamic-partition-while-loading-data-into-tables.
The quick context is that:
Load data simply copies data, it doesn't read it so it cannot figure out what to partition
Would suggest that you load data into an intermediate table first (or using an external table pointing to all the files) and then letting partition dynamic insert to kick in to load it into a partitioned table
As mentioned in #Denny Lee's answer, we need to involve a staging table(invites_stg)
managed or external and then INSERT from staging table to partitioned table(invites in this case).
Make sure we have these two properties set to:
SET hive.exec.dynamic.partition=true;
SET hive.exec.dynamic.partition.mode=nonstrict;
And finally insert to invites,
INSERT OVERWRITE TABLE India PARTITION (STATE) SELECT COL's FROM invites_stg;
Refer this link for help: http://www.edupristine.com/blog/hive-partitions-example
I worked this very same scenario, but instead, what we did is create separate HDFS data files for each partition you need to load.
Since our data is coming from a MapReduce job, we used MultipleOutputs in our Reducer class to multiplex the data into their corresponding partition file. Afterwards, it is just a matter of building the script using the Partition from the HDFS file name.
How about
LOAD DATA INPATH '/path/to/HDFS/dir/file.csv' OVERWRITE INTO TABLE DB.EXAMPLE_TABLE PARTITION (PARTITION_COL_NAME='PARTITION_VALUE');
CREATE TABLE India (
OFFICE_NAME STRING,
OFFICE_STATUS STRING,
PINCODE INT,
TELEPHONE BIGINT,
TALUK STRING,
DISTRICT STRING,
POSTAL_DIVISION STRING,
POSTAL_REGION STRING,
POSTAL_CIRCLE STRING
)
PARTITIONED BY (STATE STRING)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
STORED AS TEXTFILE;
5. Instruct hive to dynamically load partitions
SET hive.exec.dynamic.partition = true;
SET hive.exec.dynamic.partition.mode = nonstrict;

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