Hive DDL 內部表外部表 分區 分桶 行格式 存儲文件格式 概述
建立數據庫
CREATE DATABASE [IF NOT EXISTS] database_name [COMMENT database_comment] [LOCATION hdfs_path]
刪除數據庫
DROP DATABASE [IF EXISTS] database_name [RESTRICT|CASCADE]; -- RESTRICT：默認選項只能刪除空庫 -- CASCADE：能夠刪除庫和庫裏的表
建立表
建立表
CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [db_name.]table_name
[(col_name data_type [COMMENT col_comment], ...]
[COMMENT table_comment]
[PARTITIONED BY (col_name data_type [COMMENT col_comment], ...)]
[CLUSTERED BY (col_name, col_name, ...) [SORTED BY (col_name [ASC|DESC], ...)] INTO num_buckets BUCKETS]
[
[ROW FORMAT row_format]
[STORED AS file_format]
]
[LOCATION hdfs_path]
[AS select_statement];
CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [db_name.]table_name
LIKE existing_table_or_view_name
[LOCATION hdfs_path];
primitive_data_type
: TINYINT
| SMALLINT
| INT
| BIGINT
| BOOLEAN
| FLOAT
| DOUBLE
| DOUBLE PRECISION
| STRING
| BINARY
| TIMESTAMP
| DECIMAL
| DECIMAL(precision, scale)
| DATE
| VARCHAR
| CHAR
row_format
: DELIMITED [FIELDS TERMINATED BY char [ESCAPED BY char]] [COLLECTION ITEMS TERMINATED BY char]
[MAP KEYS TERMINATED BY char] [LINES TERMINATED BY char]
[NULL DEFINED AS char]
| SERDE serde_name [WITH SERDEPROPERTIES (property_name=property_value, property_name=property_value, ...)]
file_format:
: SEQUENCEFILE
| TEXTFILE -- (Default, depending on hive.default.fileformat configuration)
| RCFILE
| ORC
| PARQUET
| AVRO
| JSONFILE
| INPUTFORMAT input_format_classname OUTPUTFORMAT output_format_classname
內部表，外部表
建立時指定external時爲外部表，不然爲內部表，或者經過desc formatted table_name;輸出表的詳細信息，其中Table Type:列會輸出存儲目錄信息和數據表類型內部表（managed table），外部表（external table）java
區別：
內部表數據由Hive自身管理，外部表數據由HDFS管理；
內部表數據存儲的位置是hive.metastore.warehouse.dir（默認：/user/hive/warehouse），外部表數據的存儲位置由本身制定；
刪除內部表會直接刪除元數據（metadata）及存儲數據；刪除外部表僅僅會刪除元數據，HDFS上的文件並不會被刪除；
對內部表的修改會將修改直接同步給元數據，而對外部表的表結構和分區進行修改，則須要修復（MSCK REPAIR TABLE table_name;）
外部表：hdfs上的共享數據，多個部門公用時採用node
-- 建立內部表 create table tb_managed( id int, name string, hobby array<string>, add map<String,string> ) row format delimited fields terminated by ',' collection items terminated by '-' map keys terminated by ':' lines terminated by '\n' ; -- 數據文件及內容 complex_data_type.txt 1,xiaoming,book-TV-code,beijing:chaoyang-shagnhai:pudong 2,lilei,book-code,nanjing:jiangning-taiwan:taibei 3,lihua,music-book,heilongjiang:haerbin -- load數據 load data local inpath '/usr/local/hive-2.1.1/data_dir/complex_data_type.txt' overwrite into table tb_managed; -- 查詢表模式信息 0: jdbc:hive2://node225:10000/db01> desc formatted tb_managed; OK +-------------------------------+-------------------------------------------------------------+-----------------------+--+ | col_name | data_type | comment | +-------------------------------+-------------------------------------------------------------+-----------------------+--+ | # col_name | data_type | comment | | | NULL | NULL | | id | int | | | name | string | | | hobby | array<string> | | | add | map<string,string> | | | | NULL | NULL | | # Detailed Table Information | NULL | NULL | | Database: | db01 | NULL | | Owner: | root | NULL | | CreateTime: | Wed Oct 10 15:21:31 CST 2018 | NULL | | LastAccessTime: | UNKNOWN | NULL | | Retention: | 0 | NULL | | Location: | hdfs://ns1/user/hive/warehouse/db01.db/tb_managed | NULL | | Table Type: | MANAGED_TABLE | NULL | | Table Parameters: | NULL | NULL | | | numFiles | 1 | | | numRows | 0 | | | rawDataSize | 0 | | | totalSize | 147 | | | transient_lastDdlTime | 1539156255 | | | NULL | NULL | | # Storage Information | NULL | NULL | | SerDe Library: | org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe | NULL | | InputFormat: | org.apache.hadoop.mapred.TextInputFormat | NULL | | OutputFormat: | org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat | NULL | | Compressed: | No | NULL | | Num Buckets: | -1 | NULL | | Bucket Columns: | [] | NULL | | Sort Columns: | [] | NULL | | Storage Desc Params: | NULL | NULL | | | colelction.delim | - | | | field.delim | , | | | mapkey.delim | : | | | serialization.format | , | +-------------------------------+-------------------------------------------------------------+-----------------------+--+ 35 rows selected (0.346 seconds) -- 建立外部表 create external table tb_external( id int, name string, hobby array<string>, add map<String,string> ) row format delimited fields terminated by ',' collection items terminated by '-' map keys terminated by ':' lines terminated by '\n' location '/tmp/hive/tb_external' ; -- load數據 load data local inpath '/usr/local/hive-2.1.1/data_dir/complex_data_type.txt' overwrite into table tb_external; 0: jdbc:hive2://node225:10000/db01> desc formatted tb_external; OK +-------------------------------+-------------------------------------------------------------+-----------------------+--+ | col_name | data_type | comment | +-------------------------------+-------------------------------------------------------------+-----------------------+--+ | # col_name | data_type | comment | | | NULL | NULL | | id | int | | | name | string | | | hobby | array<string> | | | add | map<string,string> | | | | NULL | NULL | | # Detailed Table Information | NULL | NULL | | Database: | db01 | NULL | | Owner: | root | NULL | | CreateTime: | Wed Oct 10 15:39:29 CST 2018 | NULL | | LastAccessTime: | UNKNOWN | NULL | | Retention: | 0 | NULL | | Location: | hdfs://ns1/tmp/hive | NULL | | Table Type: | MANAGED_TABLE | NULL | | Table Parameters: | NULL | NULL | | | numFiles | 1 | | | totalSize | 147 | | | transient_lastDdlTime | 1539157215 | | | NULL | NULL | | # Storage Information | NULL | NULL | | SerDe Library: | org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe | NULL | | InputFormat: | org.apache.hadoop.mapred.TextInputFormat | NULL | | OutputFormat: | org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat | NULL | | Compressed: | No | NULL | | Num Buckets: | -1 | NULL | | Bucket Columns: | [] | NULL | | Sort Columns: | [] | NULL | | Storage Desc Params: | NULL | NULL | | | colelction.delim | - | | | field.delim | , | | | line.delim | \n | | | mapkey.delim | : | | | serialization.format | , | +-------------------------------+-------------------------------------------------------------+-----------------------+--+ 34 rows selected (0.22 seconds)
分區
是指按照數據的某列（值）或某些列（值）分爲多個區，形式分區即數據表的子文件夾，查詢時經過指定分區字段的值，直接從指定分區中查詢避免執行權標掃描。
建立分區表的時候，經過關鍵字 partitioned by （partition_col data_type）聲明該表是分區表，按partition_col進行分區，partition_col值一致的全部記錄存放在一個分區中，能夠依據多個列進行分區，即對某個分區的數據按照某些列繼續分區。
向分區表導入數據的時候，要經過關鍵字partition（partition_col=value）顯示聲明數據要導入到表的哪一個分區。
分區，是將知足某些條件的記錄打包，作個記號，在查詢時提升效率，在查詢時分區字段會顯示到客戶端上，但並不真正在存儲在數據表文件中，是所謂僞列。
分區表的分區會反映在文件系統中的存儲路徑，其實是在表目錄下建立了一個文件夾名爲partition_col=value，並將該區導入的數據放置該在文件夾下面。
show partitions table_name;sql
靜態分區
create table tb_partitions( id int, name string, hobby array<string>, add map<String,string> ) partitioned by (part_tag string) row format delimited fields terminated by ',' collection items terminated by '-' map keys terminated by ':' lines terminated by '\n' ; load data local inpath '/usr/local/hive-2.1.1/data_dir/complex_data_type.txt' into table tb_partitions partition(part_tag = 'first'); load data local inpath '/usr/local/hive-2.1.1/data_dir/complex_data_type.txt' into table tb_partitions partition(part_tag = 'second'); select * from tb_partitions where part_tag='first'; insert overwrite table table_name partition(partition_col=value) select ... 0: jdbc:hive2://node225:10000/db01> show partitions tb_partitions; OK +-----------------+--+ | partition | +-----------------+--+ | part_tag=first | +-----------------+--+ 1 row selected (0.278 seconds)
動態分區
hive是批處理系統，爲提升多分區插入數據的效率，hive提供了一個動態分區功能，其能夠基於查詢參數的位置去推斷分區的名稱，從而創建分區。
set hive.exec.dynamic.partition =true（默認false）,表示開啓動態分區功能? ?
set hive.exec.dynamic.partition.mode = nonstrict(默認strict),表示容許全部分區都是動態的，不然必須有靜態分區字段
系統默認以最後一個字段做爲分區名，分區須要分區的字段只能放在後面，不能把順序弄錯。系統是根據查詢字段的位置推斷分區名的，而不是字段名稱。數據庫
單字段分區
create table tb_part_dynamic_1( id int, name string, hobby array<string>, add map<String,string> ) partitioned by (tag string) row format delimited fields terminated by ',' collection items terminated by '-' map keys terminated by ':' lines terminated by '\n' ; insert overwrite table tb_part_dynamic_1 partition(tag) select id,name,hobby,add,part_tag from tb_partitions;
多字段同時靜態和動態分區
create table tb_part_dynamic_2( id int, name string, hobby array<string>, add map<String,string> ) partitioned by (categ string,tag string) row format delimited fields terminated by ',' collection items terminated by '-' map keys terminated by ':' lines terminated by '\n' ; insert overwrite table tb_part_dynamic_2 partition(categ = 'big',tag) select id,name,hobby,add,part_tag from tb_partitions;
多字段全動態分區
create table tb_part_dynamic_3( id int, name string, hobby array<string>, add map<String,string> ) partitioned by (tag1 string,tag2 string) row format delimited fields terminated by ',' collection items terminated by '-' map keys terminated by ':' lines terminated by '\n' ; insert overwrite table tb_part_dynamic_3 partition(tag1,tag2) select id,name,hobby,add,categ,tag from tb_part_dynamic_2;
分桶
相對分區進行更細粒度的劃分。分桶將整個數據內容安照某列屬性值得hash值進行區分，如要安照clustered_col屬性分爲num_buckets個桶，就是對clustered_col屬性值的hash值對num_buckets取摸，按照取模結果對數據分桶。如取模結果爲0,1,2,..num_buckets-1的數據記錄分別存放到數據表目錄下的一個文件。
分桶以前要執行命令hive.enforce.bucketiong=true;
要使用關鍵字clustered by 指定分區依據的列名，還要指定分爲多少桶num_buckets。
分桶的字段爲數據表中已有的字段，因此不用指定數據類型。
查看分桶數據須要使用tablesample。
select * from table_name tablesample(bucket 1 out of 3 on id)
能夠分桶又分區，但從文件目錄信息看不到分桶的子文件信息，能夠看到分區的目錄信息apache
0: jdbc:hive2://node225:10000/db01> set hive.enforce.bucketing=true; No rows affected (0.008 seconds) 0: jdbc:hive2://node225:10000/db01> set hive.enforce.bucketing; +------------------------------+--+ | set | +------------------------------+--+ | hive.enforce.bucketing=true | +------------------------------+--+ 1 row selected (0.016 seconds) create table tb_clusters( id int, name string, hobby array<string>, add map<String,string> ) clustered by (id) sorted by (name asc) into 2 buckets row format delimited fields terminated by ',' collection items terminated by '-' map keys terminated by ':' lines terminated by '\n' ; insert overwrite table tb_clusters select id,name,hobby,add from tb_partitions;
The CLUSTERED BY and SORTED BY creation commands do not affect how data is inserted into a table – only how it is read. bash
row_format
默認記錄和字段分隔符
- \n 每行一條記錄
- ^A 分隔列（八進制 \001）
- ^B 分隔ARRAY或者STRUCT中的元素，或者MAP中多個鍵值對之間分隔（八進制 \002）
- ^C 分隔MAP中鍵值對的「鍵」和「值」（八進制 \003）
只能使用單字符
此處經過測試有些問題，先記錄測試狀況oop
# 將正常的數據按所謂的默認分割符寫入本地文件系統
insert overwrite local directory '/usr/local/hive-2.1.1/data_dir/tb_insert_multi_02'
row format delimited
fields terminated by '^A'
collection items terminated by '^B'
map keys terminated by '^C'
lines terminated by '\n'
stored as textfile
select * from tb_insert_multi_02
;
# 本地文件狀況
[root@node225 ~]# cat /usr/local/hive-2.1.1/data_dir/tb_insert_multi_02/000000_0
1^xiaoming^book^TV^code^beijing^chaoyang^shagnhai^pudong^first^100
2^lilei^book^code^nanjing^jiangning^taiwan^taibei^first^100
3^lihua^music^book^heilongjiang^haerbin^first^100
1^xiaoming^book^TV^code^beijing^chaoyang^shagnhai^pudong^first^100
2^lilei^book^code^nanjing^jiangning^taiwan^taibei^first^100
3^lihua^music^book^heilongjiang^haerbin^first^100
# 按所謂默認分隔符建立表
create table tb_data_format(
id int,
name string,
hobby array<string>,
add map<String,string>,
tag1 string,
tag2 int
)
row format delimited
fields terminated by '^A'
collection items terminated by '^B'
map keys terminated by '^C'
lines terminated by '\n'
;
0: jdbc:hive2://node225:10000/db01> desc formatted tb_data_format;
OK
+-------------------------------+-------------------------------------------------------------+-----------------------------+--+
| col_name | data_type | comment |
+-------------------------------+-------------------------------------------------------------+-----------------------------+--+
| # col_name | data_type | comment |
| | NULL | NULL |
| id | int | |
| name | string | |
| hobby | array<string> | |
| add | map<string,string> | |
| tag1 | string | |
| tag2 | int | |
| | NULL | NULL |
| # Detailed Table Information | NULL | NULL |
| Database: | db01 | NULL |
| Owner: | root | NULL |
| CreateTime: | Thu Oct 11 16:42:25 CST 2018 | NULL |
| LastAccessTime: | UNKNOWN | NULL |
| Retention: | 0 | NULL |
| Location: | hdfs://ns1/user/hive/warehouse/db01.db/tb_data_format | NULL |
| Table Type: | MANAGED_TABLE | NULL |
| Table Parameters: | NULL | NULL |
| | COLUMN_STATS_ACCURATE | {\"BASIC_STATS\":\"true\"} |
| | numFiles | 0 |
| | numRows | 0 |
| | rawDataSize | 0 |
| | totalSize | 0 |
| | transient_lastDdlTime | 1539247345 |
| | NULL | NULL |
| # Storage Information | NULL | NULL |
| SerDe Library: | org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe | NULL |
| InputFormat: | org.apache.hadoop.mapred.TextInputFormat | NULL |
| OutputFormat: | org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat | NULL |
| Compressed: | No | NULL |
| Num Buckets: | -1 | NULL |
| Bucket Columns: | [] | NULL |
| Sort Columns: | [] | NULL |
| Storage Desc Params: | NULL | NULL |
| | colelction.delim | ^B |
| | field.delim | ^A |
| | line.delim | \n |
| | mapkey.delim | ^C |
| | serialization.format | ^A |
+-------------------------------+-------------------------------------------------------------+-----------------------------+--+
# load 數據
load data local inpath '/usr/local/hive-2.1.1/data_dir/tb_insert_multi_02/000000_0' into table tb_data_format;
# 查詢確認表中數據，並未定期望的形式加載數據
0: jdbc:hive2://node225:10000/db01> select * from tb_data_format;
OK
+--------------------+----------------------+-----------------------+---------------------+----------------------+----------------------+--+
| tb_data_format.id | tb_data_format.name | tb_data_format.hobby | tb_data_format.add | tb_data_format.tag1 | tb_data_format.tag2 |
+--------------------+----------------------+-----------------------+---------------------+----------------------+----------------------+--+
| 1 | xiaoming | ["book"] | {"TV":null} | code | NULL |
| 2 | lilei | ["book"] | {"code":null} | nanjing | NULL |
| 3 | lihua | ["music"] | {"book":null} | heilongjiang | NULL |
| 1 | xiaoming | ["book"] | {"TV":null} | code | NULL |
| 2 | lilei | ["book"] | {"code":null} | nanjing | NULL |
| 3 | lihua | ["music"] | {"book":null} | heilongjiang | NULL |
+--------------------+----------------------+-----------------------+---------------------+----------------------+----------------------+--+
# 利用默認的分隔符建立數據表，查詢表的結構信息，顯示默認的分隔符並不是所謂的「^A」等
0: jdbc:hive2://node225:10000/db01> create table tb_data_delimit(
. . . . . . . . . . . . . . . . . > id int,
. . . . . . . . . . . . . . . . . > name string,
. . . . . . . . . . . . . . . . . > hobby array<string>,
. . . . . . . . . . . . . . . . . > add map<String,string>,
. . . . . . . . . . . . . . . . . > tag1 string,
. . . . . . . . . . . . . . . . . > tag2 int
. . . . . . . . . . . . . . . . . > )
. . . . . . . . . . . . . . . . . > ;
OK
No rows affected (0.207 seconds)
0: jdbc:hive2://node225:10000/db01> desc formatted tb_data_delimit;
OK
+-------------------------------+-------------------------------------------------------------+-----------------------------+--+
| col_name | data_type | comment |
+-------------------------------+-------------------------------------------------------------+-----------------------------+--+
| # col_name | data_type | comment |
| | NULL | NULL |
| id | int | |
| name | string | |
| hobby | array<string> | |
| add | map<string,string> | |
| tag1 | string | |
| tag2 | int | |
| | NULL | NULL |
| # Detailed Table Information | NULL | NULL |
| Database: | db01 | NULL |
| Owner: | root | NULL |
| CreateTime: | Thu Oct 11 16:43:28 CST 2018 | NULL |
| LastAccessTime: | UNKNOWN | NULL |
| Retention: | 0 | NULL |
| Location: | hdfs://ns1/user/hive/warehouse/db01.db/tb_data_delimit | NULL |
| Table Type: | MANAGED_TABLE | NULL |
| Table Parameters: | NULL | NULL |
| | COLUMN_STATS_ACCURATE | {\"BASIC_STATS\":\"true\"} |
| | numFiles | 0 |
| | numRows | 0 |
| | rawDataSize | 0 |
| | totalSize | 0 |
| | transient_lastDdlTime | 1539247408 |
| | NULL | NULL |
| # Storage Information | NULL | NULL |
| SerDe Library: | org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe | NULL |
| InputFormat: | org.apache.hadoop.mapred.TextInputFormat | NULL |
| OutputFormat: | org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat | NULL |
| Compressed: | No | NULL |
| Num Buckets: | -1 | NULL |
| Bucket Columns: | [] | NULL |
| Sort Columns: | [] | NULL |
| Storage Desc Params: | NULL | NULL |
| | serialization.format | 1 |
+-------------------------------+-------------------------------------------------------------+-----------------------------+--+
# 一樣將分隔符換成「\001」等也有問題
0: jdbc:hive2://node225:10000/db01> create table tb_data_format(
. . . . . . . . . . . . . . . . . > id int,
. . . . . . . . . . . . . . . . . > name string,
. . . . . . . . . . . . . . . . . > hobby array<string>,
. . . . . . . . . . . . . . . . . > add map<String,string>,
. . . . . . . . . . . . . . . . . > tag1 string,
. . . . . . . . . . . . . . . . . > tag2 int
. . . . . . . . . . . . . . . . . > )
. . . . . . . . . . . . . . . . . > row format delimited
. . . . . . . . . . . . . . . . . > fields terminated by '\001'
. . . . . . . . . . . . . . . . . > collection items terminated by '\002'
. . . . . . . . . . . . . . . . . > map keys terminated by '\003'
. . . . . . . . . . . . . . . . . > lines terminated by '\n'
. . . . . . . . . . . . . . . . . > ;
DELIMITED性能
每一個字段之間
FIELDS TERMINATED BY char ','
集合內元素與元素之間，每組K-V對之間
COLLECTION ITEMS TERMINATED BY '-'
每組K-V對內部
MAP KEYS TERMINATED BY ':'
每條數據之間由換行符
LINES TERMINATED BY '\n'測試
SERDE
SerDe是Serialize/Deserilize的簡稱，目的是用於序列化和反序列化。
序列化是對象轉換爲字節序列的過程。
反序列化是字節序列恢復爲對象的過程。
Serialize把hive使用的java object轉換成能寫入hdfs的字節序列，或者其餘系統能識別的流文件。Deserilize把字符串或者二進制流轉換成hive能識別的java object對象。好比：select語句會用到Serialize對象， 把hdfs數據解析出來；insert語句會使用Deserilize，數據寫入hdfs系統，須要把數據序列化。
hive建立表時， 經過自定義的SerDe或使用Hive內置的SerDe類型指定數據的序列化和反序列化方式。
用row format 參數說明SerDe的類型
SerDe包括內置類型
Avro
ORC
RegEx
Thrift
Parquet
CSV
JsonSerDe
經常使用RegexSerde解析多字節分隔符
須要兩個參數：
input.regex = "(.*)::(.*)::(.*)"
output.format.string = "%1$s %2$s %3$s"編碼
create table t_user(
userid bigint comment '用戶id',
gender string comment '性別',
age int comment '年齡',
occupation string comment '職業',
zipcode string comment '郵政編碼'
)
comment '用戶信息表'
row format serde 'org.apache.hadoop.hive.serde2.RegexSerDe'
with serdeproperties('input.regex'='(.*)::(.*)::(.*)::(.*)::(.*)','output.format.string'='%1$s %2$s %3$s %4$s %5$s')
stored as textfile;
文件格式
TEXTFILE：爲默認格式，導入數據時會直接把數據文件拷貝到hdfs上不進行處理，磁盤開銷大，數據解析開銷大。
SEQUENCEFILE，RCFILE，ORCFILE格式的表不能直接從本地文件導入數據，數據要先導入到textfile格式的表中， 而後再從表中用insert導入SequenceFile,RCFile,ORCFile表中。
相比TEXTFILE和SEQUENCEFILE，RCFILE因爲列式存儲方式，數據加載時性能消耗較大，可是具備較好的壓縮比和查詢響應。數據倉庫的特色是一次寫入、屢次讀取，所以，總體來看，RCFILE相比其他兩種格式具備較明顯的優點。
SEQUENCEFILE
是Hadoop API提供的一種二進制文件支持，其具備使用方便、可分割、可壓縮的特色。支持三種壓縮選擇：NONE，RECORD，BLOCK。Record壓縮率低，通常建議使用BLOCK壓縮。
RCFILE
是一種行列存儲相結合的存儲方式。首先，其將數據按行分塊，保證同一個record在一個塊上，避免讀一個記錄須要讀取多個block。其次，塊數據列式存儲，有利於數據壓縮和快速的列存取。
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