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Docker快速安装Oracle11G,搭建oracle11g学习环境

安装说明 1.操作系统CentOS7_x64 2.安装的数据库为Oracle11G 3.已经安装了Docker环境 4.安装一些必要的软件 sh 复制代码 yum install unzip -y unzip:解压oracle安装文件 5.提前准备Oracle11G安装镜像 下载地址:https://www.oracle.com/technetwork/database/enterprise-edition/downloads/index.html 6.需要检查是否有swap分区,如果没有请设置 安装 1.镜像准备 将下载的Oracle安装包上传到指定目录并解压 如:/data0/oracle 解压命令 sh 复制代码 unzip linux.x64_11gR2_database_1of2.zip && unzip linux.x64_11gR2_database_2of2.zip 2.Docker安装 镜像准备 sh 复制代码 docker pull jaspeen/oracle-11g 启动镜像 sh 复制代码 docker run --privileged --name oracle11g -p 11030:1521 -v /data0/oracle:/install jaspeen/oracle-11g 注: /data0/oracle为刚刚Oracle解压路径 oracle11g为Docker容器名称 1521:1521为内部端口映射外部端口 等待安装结束 3.切换镜像配置密码 查看镜像是否在运行 sh 复制代码 docker ps 进入oracle11g容器 sh 复制代码 docker exec -it oracle11g /bin/bash 注:oracle11g为Docker容器名称,注意与上面对应 切换到image的oracle用户 sh 复制代码 su - oracle 进入oracle数据库 sh 复制代码 sqlplus / as sysdba 查看数据库运行状态 sh 复制代码 select status from v$instance; 修改sys用户密码 sh 复制代码 alter user sys identified by oracle; 4.外网连接测试 用户名:sys 密码:oracle 服务名:orcl 端口:1521

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英特尔深度学习框架BigDL——a distributed deep learning library for Apache Spark

BigDL: Distributed Deep Learning on Apache Spark What is BigDL? BigDL is a distributed deep learning library for Apache Spark; with BigDL, users can write their deep learning applications as standard Spark programs, which can directly run on top of existing Spark or Hadoop clusters. Rich deep learning support.Modeled afterTorch, BigDL provides comprehensive support for deep learning, including numeric computing (viaTensor) and high levelneural networks; in addition, users can load pre-trainedCaffeorTorchmodels into Spark programs using BigDL. Extremely high performance.To achieve high performance, BigDL usesIntel MKLand multi-threaded programming in each Spark task. Consequently, it is orders of magnitude faster than out-of-box open sourceCaffe,TorchorTensorFlowon a single-node Xeon (i.e., comparable with mainstream GPU). Efficiently scale-out.BigDL can efficiently scale out to perform data analytics at "Big Data scale", by leveragingApache Spark(a lightning fast distributed data processing framework), as well as efficient implementations of synchronous SGD and all-reduce communications on Spark. Why BigDL? You may want to write your deep learning programs using BigDL if: You want to analyze a large amount of data on the same Big Data (Hadoop/Spark) cluster where the data are stored (in, say, HDFS, HBase, Hive, etc.). You want to add deep learning functionalities (either training or prediction) to your Big Data (Spark) programs and/or workflow. You want to leverage existing Hadoop/Spark clusters to run your deep learning applications, which can be then dynamically shared with other workloads (e.g., ETL, data warehouse, feature engineering, classical machine learning, graph analytics, etc.) How to use BigDL? More information can be found at the BigDL project website: https://bigdl-project.github.io/ In particular, you can check out theGetting Started pagefor a quick overview of how to use BigDL For step-by-step deep leaning tutorials on BigDL (using Python), you can check out theBigDL Tutorials project You can join theBigDL Google Group(or subscribe to theMail List) for more questions and discussions on BigDL You can post bug reports and feature requests at theIssue Page 本文转自张昺华-sky博客园博客,原文链接:http://www.cnblogs.com/bonelee/p/7349523.html,如需转载请自行联系原作者

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