How to create hive table

How do you make a table like hive?

The general syntax for creating a table in Hive is: CREATE [EXTERNAL] TABLE [IF NOT EXISTS] [db_name.] table_name (col_name data_type [COMMENT ‘col_comment’],, )

Create and Load Table in Hive

  1. Step 1: Create a Database.
  2. Step 2: Create a Table in Hive.
  3. Step 3: Load Data From a File.

How do I create a hive database?

Go to Hive shell by giving the command sudo hive and enter the command ‘create database<data base name>’ to create the new database in the Hive. To list out the databases in Hive warehouse, enter the command ‘show databases‘. The database creates in a default location of the Hive warehouse.

How do I create an external Hive table?

Create a Hive External Table – Example
  1. Step 1: Prepare the Data File. Create a CSV file titled ‘countries.csv’: sudo nano countries.csv.
  2. Step 2: Import the File to HDFS. Create an HDFS directory.
  3. Step 3: Create an External Table.

How do I create a hive table from a text file?

How to load data from a text file to Hive table
  1. create table test_table (k string, v string)
  2. </code><code>row format delimited.
  3. </code><code>fields terminated by ‘\t’

How do I create a tab delimited table in hive?

HiveCreate Table
  2. Example. Let us assume you need to create a table named employee using CREATE TABLE statement.
  3. JDBC Program. The JDBC program to create a table is given example.
  4. Output. Table employee created.
  5. Syntax.
  6. Example.
  7. JDBC Program.
  8. Output:

How do I load data into a hive table?

We can load data into hive table in three ways. Two of them are DML operations of Hive. Third way is using hdfs command.

One Using Values command and other is using queries.

  1. 1.1 Using Values.
  2. 1.2 Using Queries.
  3. 2.1 From LFS to Hive Table.
  4. Using HDFS command.

Can we insert data into Hive external table?

Hive tables

It is possible to create an external table and put the data in HDFS. An external table will be created later.

What are the file formats in hive?

Hive supports several file formats:
  • Text File.
  • SequenceFile.
  • RCFile.
  • Avro Files.
  • ORC Files.
  • Parquet.

Which file format is best for hive?

Using ORC files improves performance when Hive is reading, writing, and processing data comparing to Text,Sequence and Rc. RC and ORC shows better performance than Text and Sequence File formats.

What is orc file format in hive?

The Optimized Row Columnar (ORC) file format provides a highly efficient way to store Hive data. It was designed to overcome limitations of the other Hive file formats. Using ORC files improves performance when Hive is reading, writing, and processing data.

What is SerDe in hive example?

SerDe is short for Serializer/Deserializer. The interface handles both serialization and deserialization and also interpreting the results of serialization as individual fields for processing. A SerDe allows Hive to read in data from a table, and write it back out to HDFS in any custom format.

How do I add SerDe to my hive?

Following are the steps to use it:
  1. Create a file in local file system called my_table and add following data to it:
  2. Start Hive CLI.
  3. Add the HCATALOG core file that has JSON SerDe class in it.
  4. Create a table to store JSON Data.
  5. Load JSON data to this table.
  6. Query the data.

How do I set SerDe properties in hive?

An ALTER TABLE command on a partitioned table changes the default settings for future partitions. ALTER TABLE table_name PARTITION (ing_year=2016,ing_month=8,ing_day=31) SET SERDEPROPERTIES (‘field. delim’ = ‘\u0001’);

What is difference between partitioning and bucketing in hive?

Hive partition creates a separate directory for a column(s) value. Bucketing decomposes data into more manageable or equal parts. If you go for bucketing, you are restricting number of buckets to store the data. This number is defined during table creation scripts.

Why we use bucketing in hive?

Bucketing in hive is useful when dealing with large datasets that may need to be segregated into clusters for more efficient management and to be able to perform join queries with other large datasets. The primary use case is in joining two large datasets involving resource constraints like memory limits.

Can we do bucketing without partitioning in hive?

Along with Partitioning on Hive tables bucketing can be done and even without partitioning. Moreover, Bucketed tables will create almost equally distributed data file parts.

What is the benefit of bucketing in hive?

With bucketing in Hive, you can decompose a table data set into smaller parts, making them easier to handle. Bucketing allows you to group similar data types and write them to one single file, which enhances your performance while joining tables or reading data.

How many buckets we can create in hive?

Buckets can help with the predicate pushdown since every value belonging to one value will end up in one bucket. So if you bucket by 31 days and filter for one day Hive will be able to more or less disregard 30 buckets.

Which is better partitioning or bucketing?

Hive partitioning is a technique to organize hive tables in an efficient manner. Based on partition keys it divides tables into different parts. Bucketing is a technique where the tables or partitions are further sub-categorized into buckets for better structure of data and efficient querying.

Why does partitioning optimize Hive queries?

Hive partitioning is an effective method to improve the query performance on larger tables. Partitioning allows you to store data in separate sub-directories under table location. It dramatically helps the queries which are queried upon the partition key(s).

What is the disadvantage of using too many partitions in hive tables?

Limitations: Having large number of partitions create number of files/ directories in HDFS, which creates overhead for NameNode as it maintains metadata. It may optimize certain queries based on where clause, but may cause slow response for queries based on grouping clause.

Can we create partitioning and bucketing on same column?

Bucketing can be created on just one column, you can also create bucketing on a partitioned table to further split the data which further improves the query performance of the partitioned table.