Hbase CREATE TABLE Shell command

After HBase starts, the HBase shell runs into the hbase shell command line

1. Create a table

Create ' user ', ' FName ', ' LName '

User to indicate that FName and LName are column names

2. Inserting a piece of data

Put ' user ', ' 1 ', ' FName ', ' Robin '

User is the table name, 1 is the row ID, FName is the column name, and Robin is the value of the row

Use scan ' user ' to view the results as follows

HBase (main):034:0> scan ' user '
ROW                                                  column+cell                                                                                                                                             
 1                                                   column=fname:, timestamp=1401976986832, value= Robin

Put ' user ', ' 1 ', ' LName ', ' Ma '

Use scan ' user ' to view the results as follows

HBase (main):034:0> scan ' user '
ROW                                                  column+cell                                                                                                                                             
 1                                                   column=fname:, timestamp=1401976986832, value= Robin
<pre name= "code" class= "plain" > 1                                                   column=lname:, timestamp=1401976987890, Value=ma

3. Find data by row label

Get ' user ', ' 1 '

4. View a description of the table

Describe ' user '

5. Delete a table

Drop ' user '

6. View HBase with those tables

List

About transfer from http://www.jb51.net/article/31172.htm

HBase is an open source implementation of Google BigTable, which leverages Hadoop HDFs as its file storage system, leverages Hadoop MapReduce to handle massive amounts of data in HBase, and leverages zookeeper as a collaborative service.

1. Introduction

HBase is a distributed, column-oriented, open-source database derived from a Google paper, BigTable: A distributed storage system of structured data. HBase is an open source implementation of Google BigTable, which leverages Hadoop HDFs as its file storage system, leverages Hadoop MapReduce to handle massive amounts of data in HBase, and leverages zookeeper as a collaborative service.

2. The table structure of HBase

HBase stores data in the form of a table. The table is made up of rows and columns. The columns are divided into a number of column family/column families (column family).

Row Key	Column-family1	Column-family2	Column-family3
Column1	Column2	Column1	Column2	Column3	Column1
Key1
Key2
Key3

As shown in the figure above, Key1,key2,key3 is the only row key value for three records, Column-family1,column-family2,column-family3 is a three-column family, and several columns are included under each column family. For example column-family1 This column family consists of two columns, the name is Column1 and COLUMN2,T1:ABC,T2:GDXDF is a cell that is uniquely determined by row Key1 and Column-family1-column1. There are two data in this cell, ABC and GDXDF. The timestamp of two values is different, t1,t2, and HBase returns the value of the most recent time to the requestor.

The specific meanings of these nouns are as follows:

(1) Row Key

Like NoSQL databases, row key is the primary key used to retrieve records. There are only three ways to access rows in HBase table:

(1.1) Access via a single row key

(1.2) through the range of row key

(1.3) Full table scan

Row key line keys (row key) can be any string (the maximum length is 64KB, the actual application length is generally 10-100bytes), inside HBase, the row key is saved as a byte array.

When stored, the data is sorted by the dictionary order (byte order) of the row key. When designing a key, to fully sort the storage feature, put together the row stores that are often read together. (Positional dependency)

Attention:

The result of the dictionary ordering of int is 1,10,100,11,12,13,14,15,16,17,18,19,2,20,21,..., 9,91,92,93,94,95,96,97,98,99. To maintain the natural order of shaping, the row key must be left padded with 0.

One read or write of a row is an atomic operation (no matter how many columns are read or written). This design decision makes it easy for the user to understand the behavior of the program when concurrent update operations are performed on the same row.

(2) Row Family column family

Each column in an hbase table is attributed to a column family. The column family is part of the Chema of the table (and the column is not) and must be defined before the table is used. Column names are prefixed with the column family. For example Courses:history, Courses:math belong to the courses family.

Access control, disk, and memory usage statistics are performed at the column family level. In practical applications, control permissions on the column family help us manage different types of applications: we allow some apps to add new basic data, some apps can read basic data and create inherited column families, and some apps will only allow browsing data (and maybe not even browsing all data for privacy reasons).

(3) Unit cell

A storage unit identified by row and columns in HBase is called a cell. The only unit determined by {row key, column (=<family> + <label>), version}. The data in the cell is of no type and is all stored in bytecode form.

(4) Timestamp timestamp

Each cell holds multiple versions of the same piece of data. The version is indexed by time stamp. The type of timestamp is a 64-bit integer. The timestamp can be assigned by HBase (automatically when the data is written), at which time the timestamp is the current system time that is accurate to milliseconds. Timestamps can also be explicitly assigned by the customer. If your application avoids data versioning conflicts, it must generate its own unique timestamp. In each cell, different versions of the data are sorted in reverse chronological order, that is, the most recent data is in the front row.

To avoid the burden of management (including storage and indexing) caused by too many versions of data, HBase provides two ways to recover data versions. The first is to save the last n versions of the data, and the second is to save the version for the most recent period (for example, the last seven days). Users can set them for each column family.