[hadoop] Difference between Hive internal tables and external tables?

Can anyone tell me the difference between Hive's external table and internal tables. I know the difference comes when dropping the table. I don't understand what you mean by the data and metadata is deleted in internal and only metadata is deleted in external tables. Can anyone explain me in terms of nodes please.

Also Keep in mind that Hive is a big data warehouse. When you want to drop a table you dont want to lose Gigabytes or Terabytes of data. Generating, moving and copying data at that scale can be time consuming. When you drop a 'Managed' table hive will also trash its data. When you drop a 'External' table only the schema definition from hive meta-store is removed. The data on the hdfs still remains.

An internal table data is stored in the warehouse folder, whereas an external table data is stored at the location you mentioned in table creation.

So when you delete an internal table, it deletes the schema as well as the data under the warehouse folder, but for an external table it's only the schema that you will loose.

So when you want an external table back you again after deleting it, can create a table with the same schema again and point it to the original data location. Hope it is clear now.

Hive tables can be created as EXTERNAL or INTERNAL. This is a choice that affects how data is loaded, controlled, and managed.

Use EXTERNAL tables when:

1. The data is also used outside of Hive. For example, the data files are read and processed by an existing program that doesn't lock the files.
2. Data needs to remain in the underlying location even after a DROP TABLE. This can apply if you are pointing multiple schemas (tables or views) at a single data set or if you are iterating through various possible schemas.
3. You want to use a custom location such as ASV.
4. Hive should not own data and control settings, dirs, etc., you have another program or process that will do those things.
5. You are not creating table based on existing table (AS SELECT).

Use INTERNAL tables when:

The data is temporary.

You want Hive to completely manage the lifecycle of the table and data.

To answer you Question :

For External Tables, Hive stores the data in the LOCATION specified during creation of the table(generally not in warehouse directory). If the external table is dropped, then the table metadata is deleted but not the data.

For Internal tables, Hive stores data into its warehouse directory. If the table is dropped then both the table metadata and the data will be deleted.

For your reference,

Difference between Internal & External tables :

For External Tables -

• External table stores files on the HDFS server but tables are not linked to the source file completely.

• If you delete an external table the file still remains on the HDFS server.

  As an example if you create an external table called “table_test” in HIVE using HIVE-QL and link the table to file “file”, then deleting “table_test” from HIVE will not delete “file” from HDFS.

• External table files are accessible to anyone who has access to HDFS file structure and therefore security needs to be managed at the HDFS file/folder level.

• Meta data is maintained on master node, and deleting an external table from HIVE only deletes the metadata not the data/file.

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For Internal Tables-

• Stored in a directory based on settings in hive.metastore.warehouse.dir, by default internal tables are stored in the following directory “/user/hive/warehouse” you can change it by updating the location in the config file .
• Deleting the table deletes the metadata and data from master-node and HDFS respectively.
• Internal table file security is controlled solely via HIVE. Security needs to be managed within HIVE, probably at the schema level (depends on organization).

Hive may have internal or external tables, this is a choice that affects how data is loaded, controlled, and managed.

Use EXTERNAL tables when:

• The data is also used outside of Hive. For example, the data files are read and processed by an existing program that doesn’t lock the files.
• Data needs to remain in the underlying location even after a DROP TABLE. This can apply if you are pointing multiple schema (tables or views) at a single data set or if you are iterating through various possible schema.
• Hive should not own data and control settings, directories, etc., you may have another program or process that will do those things.
• You are not creating table based on existing table (AS SELECT).

Use INTERNAL tables when:

• The data is temporary.
• You want Hive to completely manage the life-cycle of the table and data.

Source :

HDInsight: Hive Internal and External Tables Intro

Internal & external tables in Hadoop- HIVE

I would like to add that

1. Internal tables are used when the data needs to be updated or some rows need to be deleted because ACID properties can be supported on the Internal tables but ACID properties cannot be supported on the external tables.
2. Please ensure that there is a backup of the data in the Internal table because if a internal table is dropped then the data will also be lost.

The only difference in behaviour (not the intended usage) based on my limited research and testing so far (using Hive 1.1.0 -cdh5.12.0) seems to be that when a table is dropped

• the data of the Internal (Managed) tables gets deleted from the HDFS file system
• while the data of the External tables does NOT get deleted from the HDFS file system.

(NOTE: See Section 'Managed and External Tables' in https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DDL which list some other difference which I did not completely understand)

I believe Hive chooses the location where it needs to create the table based on the following precedence from top to bottom

1. Location defined during the Table Creation
2. Location defined in the Database/Schema Creation in which the table is created.
3. Default Hive Warehouse Directory (Property hive.metastore.warehouse.dir in hive.site.xml)

When the "Location" option is not used during the "creation of a hive table", the above precedence rule is used. This is applicable for both Internal and External tables. This means an Internal table does not necessarily have to reside in the Warehouse directory and can reside anywhere else.

Note: I might have missed some scenarios, but based on my limited exploration, the behaviour of both Internal and Extenal table seems to be the same except for the one difference (data deletion) described above. I tried the following scenarios for both Internal and External tables.

1. Creating table with and without Location option
2. Creating table with and without Partition Option
3. Adding new data using the Hive Load and Insert Statements
4. Adding data files to the Table location outside of Hive (using HDFS commands) and refreshing the table using the "MSCK REPAIR TABLE command
5. Dropping the tables

Internal tables are useful if you want Hive to manage the complete lifecycle of your data including the deletion, whereas external tables are useful when the files are being used outside of Hive.

INTERNAL : Table is created First and Data is loaded later

EXTERNAL : Data is present and Table is created on top of it.

In simple words, there are two things:

Hive can manage things in warehouse i.e. it will not delete data out of warehouse. When we delete table:

1) For internal tables the data is managed internally in warehouse. So will be deleted.

2) For external tables the data is managed eternal from warehouse. So can't be deleted and clients other then hive can also use it.

In external tables, if you drop it, it deletes only schema of the table, table data exists in physical location. So to deleted the data use hadoop fs - rmr tablename . Managed table hive will have full control on tables. In external tables users will have control on it.

Consider this scenario which best suits for External Table:

A MapReduce (MR) job filters a huge log file to spit out n sub log files (e.g. each sub log file contains a specific message type log) and the output i.e n sub log files are stored in hdfs.

These log files are to be loaded into Hive tables for performing further analytic, in this scenario I would recommend an External Table(s), because the actual log files are generated and owned by an external process i.e. a MR job besides you can avoid an additional step of loading each generated log file into respective Hive table as well.

When there is data already in HDFS, an external Hive table can be created to describe the data. It is called EXTERNAL because the data in the external table is specified in the LOCATION properties instead of the default warehouse directory.

When keeping data in the internal tables, Hive fully manages the life cycle of the table and data. This means the data is removed once the internal table is dropped. If the external table is dropped, the table metadata is deleted but the data is kept. Most of the time, an external table is preferred to avoid deleting data along with tables by mistake.

For managed tables, Hive controls the lifecycle of their data. Hive stores the data for managed tables in a sub-directory under the directory defined by hive.metastore.warehouse.dir by default.

When we drop a managed table, Hive deletes the data in the table.But managed tables are less convenient for sharing with other tools. For example, lets say we have data that is created and used primarily by Pig , but we want to run some queries against it, but not give Hive ownership of the data.

At that time, external table is defined that points to that data, but doesn’t take ownership of it.

In Hive We can also create an external table. It tells Hive to refer to the data that is at an existing location outside the warehouse directory. Dropping External tables will delete metadata but not the data.

The best use case for an external table in the hive is when you want to create the table from a file either CSV or text

External hive table has advantages that it does not remove files when we drop tables,we can set row formats with different settings , like serde....delimited

hive stores only the meta data in metastore and original data in out side of hive when we use external table we can give location' ' by these our original data wont effect when we drop the table