快速入手
本节将通过RPM安装物理机版本的一个Centos/Redhat 7.x单节点集群。假设我们安装的服务器hostname为oushu（可以通过命令：hostname 直接获取，请将文中所有出现的oushu替换为实际的hostname）。此次部署大约需要您30分钟时间。
安装准备
首先使用root登录。 查看有无avx指令：
cat /proc/cpuinfo | grep avx安装oushu yum源：
#Redhat/CentOS 7.0, 7.1, 7.2系统并且包含avx指令请配置以下YUM源：
wget -P /etc/yum.repos.d/ $获取的repo url
#Redhat/CentOS 7.0, 7.1, 7.2系统但不包含avx指令请配置以下YUM源：
wget -P /etc/yum.repos.d/ $获取的repo url
#Redhat/CentOS 7.3系统并且包含avx指令请配置以下YUM源：
wget -P /etc/yum.repos.d/ $获取的repo url
#Redhat/CentOS 7.3系统但不包含avx指令请配置以下YUM源：
wget -P /etc/yum.repos.d/ $获取的repo url
#Redhat/CentOS 7.4系统并且包含avx指令请配置以下YUM源：
wget -P /etc/yum.repos.d/ $获取的repo url
#Redhat/CentOS 7.4系统但不包含avx指令请配置以下YUM源：
wget -P /etc/yum.repos.d/ $获取的repo url禁用selinux：
sed -i "s/^SELINUX\=enforcing/SELINUX\=disabled/g" /etc/selinux/configsetenforce 0关闭防火墙：
systemctl stop iptablessystemctl disable iptablessystemctl stop firewalldsystemctl disable firewalld安装Java:
yum install -y java-1.8.0-openjdk java-1.8.0-openjdk-develmkdir -p /usr/java//注意查看本机的java版本ln -s /usr/lib/jvm/java-1.8.0-openjdk-1.8.0.141-2.b16.el7_4.x86_64 /usr/java/default安装HDFS
安装HDFS并且创建其使用的目录，这里我们假设我们的机器上有两个数据盘，分别mount在/data1和/data2目录，如果您有多块盘，下面的目录创建以及配置文件需要做相应的更改。尤其对HDFS的数据目录以及OushuDB的临时文件目录位置。
#由于hadoop依赖于特定版本的snappy，请先卸载snappy确保安装的顺利进行yum -y remove snappy#安装HDFS RPM，RPM安装会自动创建hdfs用户yum install -y hadoop hadoop-hdfs#在/data1上创建NameNode目录mkdir -p /data1/hdfs/namenode#在每块盘上创建DataNode数据目录，并更改权限mkdir -p /data1/hdfs/datanodechmod -R 755 /data1/hdfschown -R hdfs:hadoop /data1/hdfsmkdir -p /data2/hdfs/datanodechmod -R 755 /data2/hdfschown -R hdfs:hadoop /data2/hdfs编辑/etc/hadoop/conf/core-site.xml文件中的fs.defaultFS属性，其他系统通过这个url来访问HDFS,注：在做format之前，请确认已经将core-site.xml中fs.defaultFS的值由oushu替换成hostname。：
<property><name>fs.defaultFS</name><value>hdfs://oushu:9000</value></property>编辑 /etc/hadoop/conf/hadoop-env.sh，加入下面参数。这些参数配置了Java Home，Hadoop配置文件，日志文件目录，以及JVM选项。根据存储的HDFS数据量大小，需要适当修改NameNode的-Xmx值。HDFS数据量越大，-Xmx值应该设的越大。
export JAVA_HOME="/usr/java/default"
export HADOOP_CONF_DIR="/etc/hadoop/conf"
export HADOOP_NAMENODE_OPTS="-Xmx6144m -XX:+UseCMSInitiatingOccupancyOnly -XX:CMSInitiatingOccupancyFraction=70"
export HADOOP_DATANODE_OPTS="-Xmx2048m -Xss256k"
export HADOOP_LOG_DIR=/var/log/hadoop/$USER因为/etc/hadoop/conf/hdfs-site.xml中默认使用/data1和/data2两块盘，如果你有多块盘，你需要更改dfs.data.dir属性，使得HDFS用到所有盘：
<property><name>dfs.data.dir</name><value>/data1/hdfs/datanode,/data2/hdfs/datanode</value><final>true</final></property>格式化NameNode，并启动NameNode和DataNode。
注：在format过程中如果询问是否要format，请输入y，表示确认。
sudo -u -E hdfs hdfs namenode -formatsudo -u -E hdfs /usr/hdp/current/hadoop-client/sbin/hadoop-daemon.sh start namenodesudo -u -E hdfs /usr/hdp/current/hadoop-client/sbin/hadoop-daemon.sh start datanodeHDFS日志在/var/log/hadoop/hdfs/中。如果因为配置出错，可以查看错误日志，并依据改正。
检查hdfs是否成功运行：
su - hdfshdfs dfsadmin -reporthdfs dfs -mkdir /testnodehdfs dfs -put /usr/hdp/current/hadoop-client/sbin/hadoop-daemon.sh /testnode/hdfs dfs -ls -R /你也可以查看HDFS web界面：http://oushu:50070/
安装OushuDB
安装OushuDB RPM，OushuDB RPM安装会自动创建gpadmin用户。
yum install -y hawq在配置文件/etc/sysctl.conf添加内容
kernel.shmmax = 1000000000kernel.shmmni = 4096kernel.shmall = 4000000000kernel.sem = 250 512000 100 2048kernel.sysrq = 1kernel.core_uses_pid = 1kernel.msgmnb = 65536kernel.msgmax = 65536kernel.msgmni = 2048net.ipv4.tcp_syncookies = 0net.ipv4.conf.default.accept_source_route = 0net.ipv4.tcp_tw_recycle = 1net.ipv4.tcp_max_syn_backlog = 200000net.ipv4.conf.all.arp_filter = 1net.ipv4.ip_local_port_range = 10000 65535net.core.netdev_max_backlog = 200000fs.nr_open = 3000000kernel.threads-max = 798720kernel.pid_max = 798720# increase networknet.core.rmem_max=2097152net.core.wmem_max=2097152net.core.somaxconn=4096使系统配置生效：
sysctl -p创建OushuDB本地元数据目录和临时文件目录：
#创建OushuDB本地元数据目录，下面两个目录分别为master和segment使用mkdir -p /data1/hawq/masterddmkdir -p /data1/hawq/segmentdd#创建OushuDB临时文件目录，每块盘需要创建一个临时文件目录，这样可以让OushuDB使用到所有盘。mkdir -p /data1/hawq/tmpchmod -R 755 /data1/hawqchown -R gpadmin:gpadmin /data1/hawqmkdir -p /data2/hawq/tmpchmod -R 755 /data2/hawqchown -R gpadmin:gpadmin /data2/hawq在HDFS上创建OushuDB数据目录：
sudo -u hdfs hdfs dfs -mkdir -p /hawq_defaultsudo -u hdfs hdfs dfs -chown -R gpadmin /hawq_default编辑/usr/local/hawq/etc/slaves，去掉文件中的localhost，并加入oushu。slaves文件中存放所有slave节点的地址，每行一个节点。修改后文件为：
oushu
编辑/usr/local/hawq/etc/hawq-site.xml, 因为/usr/local/hawq/etc/hawq-site.xml中默认使用/data1和/data2两块盘，如果你有多块盘，你需要更改hawq_master_temp_directory和hawq_segment_temp_directory值，用到所有盘：
<property><name>hawq_master_address_host</name><value>oushu</value><description>The host name of hawq master.</description></property><property><name>hawq_dfs_url</name><value>oushu:9000/hawq_default</value><description>URL for accessing HDFS.</description></property><property><name>magma_nodes_url</name><value>localhost:6666</value><description>urls for accessing magma.</description></property><property><name>hawq_master_directory</name><value>/data1/hawq/masterdd</value><description>The directory of hawq master.</description></property><property><name>hawq_segment_directory</name><value>/data1/hawq/segmentdd</value><description>The directory of hawq segment.</description></property><property><name>hawq_master_temp_directory</name><value>/data1/hawq/tmp,/data2/hawq/tmp</value><description>The temporary directory reserved for hawq master. Note: please DONOT add " " between directries.</description></property><property><name>hawq_segment_temp_directory</name><value>/data1/hawq/tmp,/data2/hawq/tmp</value><description>The temporary directory reserved for hawq segment. Note: please DONOT add " " between directories.</description></property>OushuDB4.0版本新增Magma的单独配置和启停功能，使用magam服务时，首先创建magma node数据目录：
# 创建mamga node数据目录mkdir -p /data1/hawq/magma_segmentddmkdir -p /data2/hawq/magma_segmentddchown -R gpadmin:gpadmin /data1/hawqchown -R gpadmin:gpadmin /data2/hawq然后编辑配置/usr/local/hawq/etc/magma-site.xml:
<property><name>nodes_file</name><value>slaves</value><description>The magma nodes file name at GPHOME/etc</description></property><property><name>node_data_directory</name><value>file:///data1/hawq/magma_segmentdd,file:///data2/hawq/magma_segmentdd</value><description>The data directory for magma node</description></property><property><name>node_log_directory</name><value>~/hawq-data-directory/segmentdd/pg_log</value><description>The log directory for magma node</description></property><property><name>node_address_port</name><value>6666</value><description>The port magma node listening</description></property><property><name>magma_range_number</name><value>2</value></property><property><name>magma_replica_number</name><value>3</value></property><property><name>magma_datadir_capacity</name><value>3</value></property><property><name>compact_trigger_ap_ratio_limit</name><value>0.2</value><description>The threshold of triggering compact in MAGMAAP format.</description></property><property><name>compact_trigger_tp_ratio_limit</name><value>0.5</value><description>The threshold of triggering compact in MAGMAAP catalog</description></property>以gpadmin用户登录：
su - gpadmin设置免密码ssh：
source /usr/local/hawq/greenplum_path.shhawq ssh-exkeys -h oushu
初始化OushuDB，在询问是否初始化时，请输入y，表示确认初始化。
hawq init cluster //OushuDB4.0 默认不启动magma服务
hawq init cluster --with_magma //OushuDB4.0新增，3.X版本不支持该选项
// OushuDB4.0版本新增--with_magma选项，但只有hawq init|start|stop cluster命令可以带--with_magma选项。OushuDB管理工具日志在/home/gpadmin/hawqAdminLogs/中，OushuDB master日志和segment日志分别在/data1/hawq/masterdd/pg_log/ 和/data1/hawq/segmentdd/pg_log/中。如果因为配置出错，可以查看错误日志，并依据改正。
检查OushuDB是否运行正常：
su - gpadminsource /usr/local/hawq/greenplum_path.shpsql -d postgresselect * from gp_segment_configuration; //确定所有节点是up状态create table t(i int);insert into t select generate_series(1,1000);select count(*) from t;体验新执行器
本章节通过TPCH lineitem 表来展示新执行器的使用。
建立e_lineitem外部表用来生成TPCH lineitem 数据,
CREATE EXTERNAL WEB TABLE E_LINEITEM ( L_ORDERKEY INT8 ,L_PARTKEY INTEGER ,L_SUPPKEY INTEGER ,L_LINENUMBER INTEGER ,L_QUANTITY FLOAT ,L_EXTENDEDPRICE FLOAT ,L_DISCOUNT FLOAT ,L_TAX FLOAT ,L_RETURNFLAG VARCHAR(1) ,L_LINESTATUS VARCHAR(1) ,L_SHIPDATE TEXT ,L_COMMITDATE TEXT ,L_RECEIPTDATE TEXT ,L_SHIPINSTRUCT CHAR(25) ,L_SHIPMODE VARCHAR(10) ,L_COMMENT VARCHAR(44) )EXECUTE 'bash -c "$GPHOME/bin/dbgen -b $GPHOME/bin/dists.dss -T L -s 1 -N 6 -n $((GP_SEGMENT_ID + 1))"'on 6 format 'text' (delimiter '|');创建ORC 表
CREATE TABLE lineitem( L_ORDERKEY INT8,L_PARTKEY INTEGER,L_SUPPKEY INTEGER,L_LINENUMBER INTEGER,L_QUANTITY FLOAT,L_EXTENDEDPRICE FLOAT,L_DISCOUNT FLOAT,L_TAX FLOAT,L_RETURNFLAG TEXT,L_LINESTATUS TEXT,L_SHIPDATE TEXT,L_COMMITDATE TEXT,L_RECEIPTDATE TEXT,L_SHIPINSTRUCT TEXT,L_SHIPMODE TEXT,L_COMMENT TEXT)WITH (APPENDONLY = true, OIDS = FALSE, ORIENTATION = orc);插入数据
INSERT INTO lineitem SELECT * FROM e_lineitem;从下面的例子可以看到新执行器对于性能的大幅改进。
-----获取表行数------postgres=# set new_executor = on;SETpostgres=# SELECT COUNT(*) FROM lineitem;count---------6001215(1 row)Time: 17.006 mspostgres=# set new_executor = off;SETpostgres=# SELECT COUNT(*) FROM lineitem;count---------6001215(1 row)Time: 213.248 ms-----TPCH 查询 1 ------postgres=# set new_executor = on;SETpostgres=# SELECTl_returnflag,l_linestatus,sum(l_quantity)::bigint as sum_qty,sum(l_extendedprice)::bigint as sum_base_price,sum(l_extendedprice * (1 - l_discount))::bigint as sum_disc_price,sum(l_extendedprice * (1 - l_discount) * (1 + l_tax))::bigint as sum_charge,avg(l_quantity)::bigint as avg_qty,avg(l_extendedprice)::bigint as avg_price,avg(l_discount)::bigint as avg_disc,count(*) as count_orderFROMlineitemWHEREl_shipdate <= '1998-08-20'GROUP BYl_returnflag,l_linestatus;l_returnflag | l_linestatus | sum_qty | sum_base_price | sum_disc_price | sum_charge | avg_qty | avg_price | avg_disc | count_order--------------+--------------+----------+----------------+----------------+--------------+---------+-----------+----------+-------------R | F | 37719753 | 56568041381 | 53741292685 | 55889619120 | 26 | 38251 | 0 | 1478870N | F | 991417 | 1487504710 | 1413082168 | 1469649223 | 26 | 38284 | 0 | 38854A | F | 37734107 | 56586554401 | 53758257135 | 55909065223 | 26 | 38273 | 0 | 1478493N | O | 73808911 | 110700990251 | 105167436999 | 109377979031 | 26 | 38248 | 0 | 2894278(4 rows)Time: 234.376 mspostgres=# set new_executor = off;SETpostgres=# SELECTl_returnflag,l_linestatus,sum(l_quantity)::bigint as sum_qty,sum(l_extendedprice)::bigint as sum_base_price,sum(l_extendedprice * (1 - l_discount))::bigint as sum_disc_price,sum(l_extendedprice * (1 - l_discount) * (1 + l_tax))::bigint as sum_charge,avg(l_quantity)::bigint as avg_qty,avg(l_extendedprice)::bigint as avg_price,avg(l_discount)::bigint as avg_disc,count(*) as count_orderFROMlineitemWHEREl_shipdate <= '1998-08-20'GROUP BYl_returnflag,l_linestatus;l_returnflag | l_linestatus | sum_qty | sum_base_price | sum_disc_price | sum_charge | avg_qty | avg_price | avg_disc | count_order--------------+--------------+----------+----------------+----------------+--------------+---------+-----------+----------+-------------R | F | 37719753 | 56568041381 | 53741292685 | 55889619120 | 26 | 38251 | 0 | 1478870N | F | 991417 | 1487504710 | 1413082168 | 1469649223 | 26 | 38284 | 0 | 38854A | F | 37734107 | 56586554401 | 53758257135 | 55909065223 | 26 | 38273 | 0 | 1478493N | O | 73808911 | 110700990251 | 105167436999 | 109377979031 | 26 | 38248 | 0 | 2894278(4 rows)Time: 2341.147 ms
