I am a little confused on where does the hive stores it's data.
Does it stores it's data in HDFS or in a RDBMS ??
Does Hive Meta store uses a RDBMS to store the hive tables metadata ??
Thanks in Advance !!
Hive data are stored in one of Hadoop compatible filesystem: S3, HDFS or other compatible filesystem.
Hive metadata are stored in RDBMS like MySQL, see supported RDBMS.
The location of Hive tables data in S3 or HDFS can be specified for both managed and external tables.
The difference between managed and external tables is that DROP TABLE statement, in managed table, will drop the table and delete table's data. Whereas, for external table DROP TABLE will drop only the table and data will remain as is and can be used for creating other tables over it.
See details here: Create/Drop/Truncate Table
Here is the answer to your question. But I will suggest you to read hive books or apache hive site for better understanding.
Does it stores it's data in HDFS or in a RDBMS ?? - The Data for HIVE is always stored in HDFS. For managed tables the data is stored in hive warehouse by default which is a directory in HDFS. For HIVE External table user can specify the location anywhere in HDFS.
Does Hive Meta store uses a RDBMS to store the hive tables metadata ?? - Yes HIVE uses RDBMS to store the metadata.
Related
I'm new to hive and read about it online too. But still having doubts which are not cleared.
for hive external tables, hive keep table's metadata within HDFS, but not in its warehouse which is also in HDFS. correct ?
whether its internal or external table, in both cases data of table will be available in HDFS only but NOWHERE else. Mean to say, data can taken from anywhere but has to be loaded in HDFS, because HIVE uses hadoop's processing engine to process data. Correct ?
internal table, table's metadata and table's data both will be available in HIVE's data warehouse, and this data warehouse will be at nowhere else but in HDFS only. correct ?
in external table, table's metadata and table's data both will be NOT available in HIVE's data warehouse but in HDFS. But hive must be keeping some info with itself that where is table's metadata located and where is its data located in HDFS, correct ?
Can anyone share feedback to above understanding ?
THanks
Hive uses relational database like MySQL, MariaDB, PostgreSQL, Oracle, DerbyDB(for embedded deployment only) for storing metadata (databases, tables definitions, statistics, grants, etc). See deployment modes and database requirements. Does not matter Internal or external table, the metadata are stored in the relational database.
Yes, the data is stored in HDFS, but also Hive supports integration with external databases using JDBC storage handler. Such table looks like normal Hive table, but the data is stored in some database, your queries executed in the database, predicate push-down works, you can use hive native tables with storage handler tables in single query. Also HBase storage handler is available, Kafka storage handler, etc, you can write your own storage handler.
Depending on your Hive version/vendor It is possible to create many tables (both managed and external at the same time) on top of the same location in HDFS. Though Cloudera prefers to have managed tables in dedicated HDFS location for them, see https://stackoverflow.com/a/67073849/2700344 and does not allow to specify location for managed tables outside the warehouse root by default. Read abot the difference between managed and external tables here.
Everything seems correct except last one. When you create external table table metadata will be stored in the Hive otherwise you can not query through hive. HDFS itself keeps control of your data when you create external table. While when you create internal table Hive will be responsible. Dropping internal table drops your data and metadata but dropping external table only drops metadata from Hive. But your data will be remain inside of your file system. Thats why we are changing table types a lot as a workaround when some of our external connection is not compatible with our hive version.
I am a little confused on the purpose of the MetaStore. When you create a table in hive:
CREATE TABLE <table_name> (column1 data_type, column2 data_type);
LOAD DATA INPATH <HDFS_file_location> INTO table managed_table;
So I know this command takes the contents of the file in HDFS and creates a MetaData form of it and stores it in the MetaStore (including column types, column names, the place where it is in HDFS, etc. of each row in the HDFS file). It doesn't actually move the data from HDFS into Hive.
But what is the purpose of storing this MetaData?
When I connect to Hive using Spark SQL for example the MetaStore doesn't contain the actual information in HDFS but just MetaData. So is the MetaStore simply used by Hive to do parsing and compiling steps against the HiveQL query and to create the MapReduce jobs?
Metastore is for storing schema(table definitions including location in HDFS, serde, columns, comments, types, partition definitions, views, access permissions, etc) and statistics. There is no such operation as moving data from HDFS to Hive because Hive tables data is stored in HDFS(or other compatible filesystem like S3). You can define new table or even few tables on top of some location in HDFS and put files in it. You can change existing table location or partition location, all this information is stored in the metastore, so Hive knows how to access data. Table is a logical object defined in the metastore and data itself are just files in some location in HDFS.
See also this answer about Hive query execution flow(high level): https://stackoverflow.com/a/45587873/2700344
Hive performs schema-on-read operations, which means that for the data to be processed in some structured manner (i.e. a table-like object), the layout of said data needs to be summarized in a relational structure
takes the contents of the file in HDFS and creates a MetaData form of it
As far as I know, no files are actually read when you create a table.
SparkSQL connects to the metastore directly. Both Spark and HiveServer have their own query parsers. It's not part of the metastore. MapReduce/Tez/Spark jobs are also not handled by the metastore. It's just a relational database. If it's Mysql, Postgres, or Oracle, you can easily go connect to it and inspect the contents. By default, both Hive and Spark use an embedded Derby database
I added a CSV file in HDFS using R script.
I update this CSV with new CSV/append data to it
Created table using hue in Hive over this CSV.
Altered it to be an external table.
Now, if when data is changed in the hdfs location, would data be automatically updated in hive table?
That's the thing with external (and also managed) tables in Hive. They're not really tables. You can think of them as link to HDFS location. So whenever you query external table, Hive reads all the data from location you selected when you created this table.
From Hive doc:
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.
I am fairly new to Hadoop (HDFS and Hbase) and Hadoop Eco system (Hive, Pig, Impala etc.). I have got a good understanding of Hadoop components such as NamedNode, DataNode, Job Tracker, Task Tracker and how they work in tandem to store the data in efficient manner.
While trying to understand fundamentals of data access layer such as Hive, I need to understand where exactly a table’s data (created in Hive) gets stored? We can create external and internal table in Hive. As external tables can be in HDFS or any other file system, Hive doesnt store data for such tables in warehouse. What about internal tables? This table will be created as a directory on one of the data nodes on Hadoop Cluster. Once we load data in these tables from local or HDFS file system, are there further files getting created to store data in tables created in Hive?
Say for example:
A sample file named test_emp_feedback.csv was brought from local file system to HDFS.
A table (emp_feedback) was created in Hive with a structure similar to csv file structure. This lead to creation of a directory in Hadoop cluster say /users/big_data/hive/emp_feedback
Now once I create the table and load data in emp_feedback table from test_emp_feedback.csv
Is Hive going to create a copy of file in emp_feedback directory? Wont it cause data redundancy?
Creating a Managed table will create a directory with Same name as table name at Hive warehouse directory(Usually at /user/hive/warehouse/dbname/tablename).Also the table structure(Hive Metadata) is created in the metastore(RDBMS/HCat).
Before you load the data on the table, this directory(with the same name as table name under hive warehouse) is empty.
There could be 2 possible scenarios.
If the table is external the data is not copied to warehouse directory at all.
If the table is managed(not external), when you load your data to the table it is moved(not Copied) from current HDFS location to Hive warehouse directory9/user/hive/warehouse//). So this will not replicate the data.
Caution: It is always advisable to create external table unless the data is only used by hive. Dropping a managed table would delete the data from HDFS(Warehouse of HIVE).
HadoopGig
To answer you Question :
For External Tables:
Hive does not move the data into its warehouse directory. If the external table is dropped, then the table metadata is deleted but not the data.
For Internal tables
Hive moves data into its warehouse directory. If the table is dropped, then 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.
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
It would not cause data redundancy. For managed (not external) tables Hive moves the data into its warehouse directory. In your example, the data will be moved from original location on HDFS to '/users/big_data/hive/emp_feedback'.
Be careful with the removal of the managed table, it will lead to removal data on HDFS also.
You can send data in two days
A) use LOAD DATA INPATH 'file_location_of_csv' INTO TABLE emp_feedback;
Note that this command will remove content at source directory and create a internal table
OR)
B) Use copyFromLocal or put command to copy local file into HDFS and then create external table and copy the data into table. Now data won't be moved from source. You can drop external table but still source data is available.
e.g.
create external table emp_feedback (
emp_id int,
emp_name string
)
location '/location_in_hdfs_for_csv file';
When you drop an external table, it only drops the meta data of HIVE table. Data still exists at HDFS file location.
Got it. This is what I was able to understand so far.
It all depends upon which type of table is being created and where from the file is picked up. Below are possible use cases
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I am using hive v0.13
My data is stored in hdfs, I use create "CREATE external TABLE" to create a table for those data. Everything works fine, I can issue "select" statements. The question is under the warehouse directory (hive.metastore.warehouse.dir), I don't see any files/data get added, is this normal? I know with "external" table data will not get copy to warehouse directory but shouldn't there be table meta data be stored under there?
When you create a internal table hive creates a directory with table name under the directory you have specified in hive.metastore.warehouse.dir. For me it /apps/hive/warehouse.
Suppose you have created a table name test_tbl then there will be a directory /apps/hive/warehouse/test_tbland hive store metadata into mysql or your configured RDBMS for store metadata.and when you load data using LOAD DATA INPATH command into this directory.
But in external table you specify a location in your create statement hence hive doesn't create any directory in default warehouse directory because you have already provided the location. it just store metadata information in RDBMS
You can directly load data into that location using hdfs dfs -put command and hive will treat that data for the table which is associated with that particular directory. Hence it is expected behavior for external table.
when you create a external table Metadata will be genrally stored in the RDBMS i.e., in metastore database and the data which you insert or load will be stored in the directory.
either it is an external or managed table metadata will always be in RDBMS when you query on any table hive will actually get the table schema from metastore and data from HDFS evaluates the schema with data and displays.
So, there wont be any metadata created in warehouse for external tables.