組件安排以下:java
172.16.57.75 bd-ops-test-75 mysql-server 172.16.57.77 bd-ops-test-77 Hiveserver2 HiveMetaStore
在77上安裝hive:node
# yum install hive hive-metastore hive-server2 hive-jdbc hive-hbase -y
在其餘節點上能夠安裝客戶端:mysql
# yum install hive hive-server2 hive-jdbc hive-hbase -y
yum方式安裝mysql:sql
# yum install mysql mysql-devel mysql-server mysql-libs -y
啓動數據庫:shell
# 配置開啓啓動 # chkconfig mysqld on # service mysqld start
安裝jdbc驅動:數據庫
# yum install mysql-connector-java # ln -s /usr/share/java/mysql-connector-java.jar /usr/lib/hive/lib/mysql-connector-java.jar
設置mysql初始密碼爲bigdata:apache
# mysqladmin -uroot password 'bigdata'
進入數據庫後執行以下:vim
CREATE DATABASE metastore; USE metastore; SOURCE /usr/lib/hive/scripts/metastore/upgrade/mysql/hive-schema-1.1.0.mysql.sql; CREATE USER 'hive'@'localhost' IDENTIFIED BY 'hive'; GRANT ALL PRIVILEGES ON metastore.* TO 'hive'@'localhost'; GRANT ALL PRIVILEGES ON metastore.* TO 'hive'@'%'; FLUSH PRIVILEGES;
注意:建立的用戶爲 hive,密碼爲 hive ,你能夠按本身須要進行修改。bash
修改 hive-site.xml 文件中如下內容:app
<property> <name>javax.jdo.option.ConnectionURL</name> <value>jdbc:mysql://172.16.57.75:3306/metastore?useUnicode=true&characterEncoding=UTF-8</value> </property> <property> <name>javax.jdo.option.ConnectionDriverName</name> <value>com.mysql.jdbc.Driver</value> </property>
修改/etc/hadoop/conf/hadoop-env.sh
,添加環境變量 HADOOP_MAPRED_HOME
,若是不添加,則當你使用 yarn 運行 mapreduce 時候會出現 UNKOWN RPC TYPE
的異常
export HADOOP_MAPRED_HOME=/usr/lib/hadoop-mapreduce
在 hdfs 中建立 hive 數據倉庫目錄:
/user/hive/warehouse
,建議修改其訪問權限爲 1777
,以便其餘全部用戶均可以建立、訪問表,但不能刪除不屬於他的表。/user
目錄下,如 root 用戶的爲 /user/root
)/tmp
必須是 world-writable 權限的。建立目錄並設置權限:
# sudo -u hdfs hadoop fs -mkdir /user/hive # sudo -u hdfs hadoop fs -chown hive /user/hive # sudo -u hdfs hadoop fs -mkdir /user/hive/warehouse # sudo -u hdfs hadoop fs -chmod 1777 /user/hive/warehouse # sudo -u hdfs hadoop fs -chown hive /user/hive/warehouse
修改hive-env設置jdk環境變量 :
# vim /etc/hive/conf/hive-env.sh export JAVA_HOME=/opt/programs/jdk1.7.0_67
啓動hive-server和metastore:
# service hive-metastore start # service hive-server2 start
$ hive -e'create table t(id int);' $ hive -e'select * from t limit 2;' $ hive -e'select id from t;'
訪問beeline:
$ beeline beeline> !connect jdbc:hive2://localhost:10000;
先安裝 hive-hbase:
# yum install hive-hbase -y
若是你是使用的 cdh4,則須要在 hive shell 裏執行如下命令添加 jar:
$ ADD JAR /usr/lib/hive/lib/zookeeper.jar; $ ADD JAR /usr/lib/hive/lib/hbase.jar; $ ADD JAR /usr/lib/hive/lib/hive-hbase-handler-<hive_version>.jar # guava 包的版本以實際版本爲準。 $ ADD JAR /usr/lib/hive/lib/guava-11.0.2.jar;
若是你是使用的 cdh5,則須要在 hive shell 裏執行如下命令添加 jar:
ADD JAR /usr/lib/hive/lib/zookeeper.jar; ADD JAR /usr/lib/hive/lib/hive-hbase-handler.jar; ADD JAR /usr/lib/hbase/lib/guava-12.0.1.jar; ADD JAR /usr/lib/hbase/hbase-client.jar; ADD JAR /usr/lib/hbase/hbase-common.jar; ADD JAR /usr/lib/hbase/hbase-hadoop-compat.jar; ADD JAR /usr/lib/hbase/hbase-hadoop2-compat.jar; ADD JAR /usr/lib/hbase/hbase-protocol.jar; ADD JAR /usr/lib/hbase/hbase-server.jar;
以上你也能夠在 hive-site.xml 中經過 hive.aux.jars.path
參數來配置,或者你也能夠在 hive-env.sh 中經過 export HIVE_AUX_JARS_PATH=
來設置。
與Hive相似,Impala也能夠直接與HDFS和HBase庫直接交互。只不過Hive和其它創建在MapReduce上的框架適合須要長時間運行的批處理任務。例如:那些批量提取,轉化,加載(ETL)類型的Job,而Impala主要用於實時查詢。
組件分配以下:
172.16.57.74 bd-ops-test-74 impala-state-store impala-catalog impala-server 172.16.57.75 bd-ops-test-75 impala-server 172.16.57.76 bd-ops-test-76 impala-server 172.16.57.77 bd-ops-test-77 impala-server
在74節點安裝:
yum install impala-state-store impala-catalog impala-server -y
在7五、7六、77節點上安裝:
yum install impala-server -y
查看安裝路徑:
# find / -name impala /var/run/impala /var/lib/alternatives/impala /var/log/impala /usr/lib/impala /etc/alternatives/impala /etc/default/impala /etc/impala /etc/default/impala
impalad的配置文件路徑由環境變量IMPALA_CONF_DIR
指定,默認爲/usr/lib/impala/conf
,impala 的默認配置在/etc/default/impala,修改該文件中的 IMPALA_CATALOG_SERVICE_HOST
和 IMPALA_STATE_STORE_HOST
IMPALA_CATALOG_SERVICE_HOST=bd-ops-test-74 IMPALA_STATE_STORE_HOST=bd-ops-test-74 IMPALA_STATE_STORE_PORT=24000 IMPALA_BACKEND_PORT=22000 IMPALA_LOG_DIR=/var/log/impala IMPALA_CATALOG_ARGS=" -log_dir=${IMPALA_LOG_DIR} -sentry_config=/etc/impala/conf/sentry-site.xml" IMPALA_STATE_STORE_ARGS=" -log_dir=${IMPALA_LOG_DIR} -state_store_port=${IMPALA_STATE_STORE_PORT}" IMPALA_SERVER_ARGS=" \ -log_dir=${IMPALA_LOG_DIR} \ -use_local_tz_for_unix_timestamp_conversions=true \ -convert_legacy_hive_parquet_utc_timestamps=true \ -catalog_service_host=${IMPALA_CATALOG_SERVICE_HOST} \ -state_store_port=${IMPALA_STATE_STORE_PORT} \ -use_statestore \ -state_store_host=${IMPALA_STATE_STORE_HOST} \ -be_port=${IMPALA_BACKEND_PORT} \ -server_name=server1\ -sentry_config=/etc/impala/conf/sentry-site.xml" ENABLE_CORE_DUMPS=false # LIBHDFS_OPTS=-Djava.library.path=/usr/lib/impala/lib # MYSQL_CONNECTOR_JAR=/usr/share/java/mysql-connector-java.jar # IMPALA_BIN=/usr/lib/impala/sbin # IMPALA_HOME=/usr/lib/impala # HIVE_HOME=/usr/lib/hive # HBASE_HOME=/usr/lib/hbase # IMPALA_CONF_DIR=/etc/impala/conf # HADOOP_CONF_DIR=/etc/impala/conf # HIVE_CONF_DIR=/etc/impala/conf # HBASE_CONF_DIR=/etc/impala/conf
設置 impala 可使用的最大內存:在上面的 IMPALA_SERVER_ARGS
參數值後面添加 -mem_limit=70%
便可。
若是須要設置 impala 中每個隊列的最大請求數,須要在上面的 IMPALA_SERVER_ARGS
參數值後面添加 -default_pool_max_requests=-1
,該參數設置每個隊列的最大請求數,若是爲-1,則表示不作限制。
在節點74上建立hive-site.xml
、core-site.xml
、hdfs-site.xml
的軟連接至/etc/impala/conf
目錄並做下面修改在hdfs-site.xml
文件中添加以下內容:
<property> <name>dfs.client.read.shortcircuit</name> <value>true</value> </property> <property> <name>dfs.domain.socket.path</name> <value>/var/run/hadoop-hdfs/dn._PORT</value> </property> <property> <name>dfs.datanode.hdfs-blocks-metadata.enabled</name> <value>true</value> </property>
同步以上文件到其餘節點。
在每一個節點上建立/var/run/hadoop-hdfs:
# mkdir -p /var/run/hadoop-hdfs
impala 安裝過程當中會建立名爲 impala 的用戶和組,不要刪除該用戶和組。
若是想要 impala 和 YARN 和 Llama 合做,須要把 impala 用戶加入 hdfs 組。
impala 在執行 DROP TABLE 操做時,須要把文件移到到 hdfs 的回收站,因此你須要建立一個 hdfs 的目錄 /user/impala,並將其設置爲impala 用戶可寫。一樣的,impala 須要讀取 hive 數據倉庫下的數據,故須要把 impala 用戶加入 hive 組。
impala 不能以 root 用戶運行,由於 root 用戶不容許直接讀。
建立 impala 用戶家目錄並設置權限:
sudo -u hdfs hadoop fs -mkdir /user/impala sudo -u hdfs hadoop fs -chown impala /user/impala
查看 impala 用戶所屬的組:
# groups impala impala : impala hadoop hdfs hive
由上可知,impala 用戶是屬於 imapal、hadoop、hdfs、hive 用戶組的 。
在 74節點啓動:
# service impala-state-store start # service impala-catalog start
使用impala-shell
啓動Impala Shell,鏈接 74,並刷新元數據
#impala-shell Starting Impala Shell without Kerberos authentication Connected to bd-dev-hadoop-70:21000 Server version: impalad version 2.3.0-cdh5.5.1 RELEASE (build 73bf5bc5afbb47aa7eab06cfbf6023ba8cb74f3c) *********************************************************************************** Welcome to the Impala shell. Copyright (c) 2015 Cloudera, Inc. All rights reserved. (Impala Shell v2.3.0-cdh5.5.1 (73bf5bc) built on Wed Dec 2 10:39:33 PST 2015) After running a query, type SUMMARY to see a summary of where time was spent. *********************************************************************************** [bd-dev-hadoop-70:21000] > invalidate metadata;
當在 Hive 中建立表以後,第一次啓動 impala-shell 時,請先執行 INVALIDATE METADATA
語句以便 Impala 識別出新建立的表(在 Impala 1.2 及以上版本,你只須要在一個節點上運行 INVALIDATE METADATA
,而不是在全部的 Impala 節點上運行)。
你也能夠添加一些其餘參數,查看有哪些參數:
#impala-shell -h Usage: impala_shell.py [options] Options: -h, --help show this help message and exit -i IMPALAD, --impalad=IMPALAD <host:port> of impalad to connect to [default: bd-dev-hadoop-70:21000] -q QUERY, --query=QUERY Execute a query without the shell [default: none] -f QUERY_FILE, --query_file=QUERY_FILE Execute the queries in the query file, delimited by ; [default: none] -k, --kerberos Connect to a kerberized impalad [default: False] -o OUTPUT_FILE, --output_file=OUTPUT_FILE If set, query results are written to the given file. Results from multiple semicolon-terminated queries will be appended to the same file [default: none] -B, --delimited Output rows in delimited mode [default: False] --print_header Print column names in delimited mode when pretty- printed. [default: False] --output_delimiter=OUTPUT_DELIMITER Field delimiter to use for output in delimited mode [default: \t] -s KERBEROS_SERVICE_NAME, --kerberos_service_name=KERBEROS_SERVICE_NAME Service name of a kerberized impalad [default: impala] -V, --verbose Verbose output [default: True] -p, --show_profiles Always display query profiles after execution [default: False] --quiet Disable verbose output [default: False] -v, --version Print version information [default: False] -c, --ignore_query_failure Continue on query failure [default: False] -r, --refresh_after_connect Refresh Impala catalog after connecting [default: False] -d DEFAULT_DB, --database=DEFAULT_DB Issues a use database command on startup [default: none] -l, --ldap Use LDAP to authenticate with Impala. Impala must be configured to allow LDAP authentication. [default: False] -u USER, --user=USER User to authenticate with. [default: root] --ssl Connect to Impala via SSL-secured connection [default: False] --ca_cert=CA_CERT Full path to certificate file used to authenticate Impala's SSL certificate. May either be a copy of Impala's certificate (for self-signed certs) or the certificate of a trusted third-party CA. If not set, but SSL is enabled, the shell will NOT verify Impala's server certificate [default: none] --config_file=CONFIG_FILE Specify the configuration file to load options. File must have case-sensitive '[impala]' header. Specifying this option within a config file will have no effect. Only specify this as a option in the commandline. [default: /root/.impalarc] --live_summary Print a query summary every 1s while the query is running. [default: False] --live_progress Print a query progress every 1s while the query is running. [default: False] --auth_creds_ok_in_clear If set, LDAP authentication may be used with an insecure connection to Impala. WARNING: Authentication credentials will therefore be sent unencrypted, and may be vulnerable to attack. [default: none]
使用 impala 導出數據:
impala-shell -i '172.16.57.74:21000' -r -q "select * from test" -B --output_delimiter="\t" -o result.txt