I have a production hive table partitioned by date. New data are generated hourly, and I need to merge the new data into the hive table.
In case there're duplicate data insertion requests or data overlap among hourly requests, I want to perform dedup to each partition whenever I update it.
I reviewed the answer to How to Append new data to already existing hive table
, but still have some confusions:
How should I merge the new data pieces into the existing partition?
I mean, should I create a tmp table for the new data, pull existing data into the tmp table, make dudup and OVERWRITE back the partition of the production table?
Is it possible "dirty read" could occur during the overwriting of the partition of the production hive table? Is there any solution to this?
I'm wondering if there's anything like atomic RENAME.
Can anyone please explain why and where do we use external tables in hive?
Please explain a scenario to understand easily.
We use external table when our underlying dataset pointed by hive table is shared by many purpose i.e for map reduce job, pig etc and use managed table in hive when our dataset pointed by hive table is used only by hive application.
Actually in hive managed table has full control on dataset i.e in managed table if you will drop the table dataset will also be deleted from hive warehouse(/usr/hive/warehouse) present in HDFS, but in case of external table when you drop the table, dataset are not deleted from hive warehouse in HDFS.
Suppose take an example you have 50 gb data set now if you create multiple copies of dataset for different purpose it will simply take more space so the better option is to use external table so that when you drop the table dataset are not deleted and you can use it further by any other application like by pig or by any other purpose.
As a rule of thumb: use external table if you plan to work with those data not only from Hive but from other frameworks as well. Otherwise make it internal.
The only difference between External and Managed table in Hive is Drop table or Drop partition behavior. For Managed it will drop data as well, for External table the data will remain untouched in the table/partition location.
Use External in most cases. External table allows you to change table definition easily. Also you can create few tables on top of the same location.
Use Managed table if the table is temporary/intermediate and data should be deleted to free space.
Managed table can be converted to external and vice-versa using
alter table table_name SET TBLPROPERTIES('EXTERNAL'='TRUE');
We are stuck with a problem where-in we are trying to do a near real time sync between a RDBMS(Source) and hive (Target). Basically the source is pushing the changes (inserts, updates and deletes) into HDFS as avro files. These are loaded into external tables (with avro schema), into the Hive. There is also a base table in ORC, which has all the records that came in before the Source pushed in the new set of records.
Once the data is received, we have to do a de-duplication (since there could be updates on existing rows) and remove all deleted records (since there could be deletes from the Source).
We are now performing a de-dupe using rank() over partitioned keys on the union of external table and base table. And then the result is then pushed into a new table, swap the names. This is taking a lot of time.
We tried using merges, acid transactions, but rank over partition and then filtering out all the rows has given us the best possible time at this moment.
Is there a better way of doing this? Any suggestions on improving the process altogether? We are having quite a few tables, so we do not have any partitions or buckets at this moment.
You can try with storing all the transactional data into Hbase table.
Storing data into Hbase table using Primary key of RDBMS table as Row Key:-
Once you pull all the data from RDBMS with NiFi processors(executesql,Querydatabasetable..etc) we are going to have output from the processors in Avro format.
You can use ConvertAvroToJson processor and then use SplitJson Processor to split each record from array of json records.
Store all the records in Hbase table having Rowkey as the Primary key in the RDBMS table.
As when we get incremental load based on Last Modified Date field we are going to have updated records and newly added records from the RDBMS table.
If we got update for the existing rowkey then Hbase will overwrite the existing data for that record, for newly added records Hbase will add them as a new record in the table.
Then by using Hive-Hbase integration you can get the Hbase table data exposed using Hive.
https://cwiki.apache.org/confluence/display/Hive/HBaseIntegration
By using this method we are going to have Hbase table that will take care of all the upsert operations and we cannot expect same performance from hive-hbase table vs native hive table will perform faster,as hbase tables are not meant for sql kind of queries, hbase table is most efficient if you are accessing data based on Rowkey,
if we are going to have millions of records then we need to do some tuning to the hive queries
Tuning Hive Queries That Uses Underlying HBase Table
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.
Hive has a relational database on the master node it uses to keep track of state.
For instance, when you CREATE TABLE FOO(foo string) LOCATION 'hdfs://tmp/';, this table schema is stored in the database.
If you have a partitioned table, the partitions are stored in the database(this allows hive to use lists of partitions without going to the file-system and finding them, etc). These sorts of things are the 'metadata'.
When you drop an internal table, it drops the data, and it also drops the metadata.
When you drop an external table, it only drops the meta data. That means hive is ignorant of that data now. It does not touch the data itself.
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:
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 schemas (tables or views) at a single data set or if you are iterating through various possible schemas.
You want to use a custom location such as ASV.
Hive should not own data and control settings, dirs, etc., you 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 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.
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
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.
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
Location defined during the Table Creation
Location defined in the Database/Schema Creation in which the table is created.
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.
Creating table with and without Location option
Creating table with and without Partition Option
Adding new data using the Hive Load and Insert Statements
Adding data files to the Table location outside of Hive (using HDFS commands) and refreshing the table using the "MSCK REPAIR TABLE command
Dropping the tables
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.
INTERNAL : Table is created First and Data is loaded later
EXTERNAL : Data is present and Table is created on top of it.
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.
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
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.
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.
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
Both Internal and External tables are owned by HIVE. The only difference being the ownership of data. The commands for creating both tables are shown below. Only an additional EXTERNAL keyword comes in case of external table creation. Both tables can be created/deleted/modified using SQL Statements.
In case of Internal Tables, both the table and the data contained in the tables are managed by HIVE. That is, we can add/delete/modify any data using HIVE. When we DROP the table, along with the table, the data will also get deleted.
Eg: CREATE TABLE tweets (text STRING, words INT, length INT) ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' STORED AS TEXTFILE;
In case of External Tables, only the table is managed by HIVE. The data present in these tables can be from any storage locations like HDFS. We cant add/delete/modify the data in these tables. We can only use the data in these tables using SELECT statements. When we DROP the table, only the table gets deleted and not the data contained in it. This is why its said that only meta-data gets deleted. When we create EXTERNAL tables, we need to mention the location of the data.
Eg: CREATE EXTERNAL TABLE tweets (text STRING, words INT, length INT) ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' STORED AS TEXTFILE LOCATION '/user/hive/warehouse/tweets';
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
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.
I would like to add that
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.
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.
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.