使用Jerry這篇文章在Google Cloud platform上的Kubernetes集群部署HANA Express里介紹的方法在Google Cloud Platform的Kubernetes cluster上安裝SAP HANA Express.

文中介紹了一個yaml文件，里面聲明了容器鏡像文件store/saplabs/hanaexpress:2.00.033.00.20180925.2.

安裝完成后，在啟動的pod里有兩個容器，分別運行著SQLPad和HANA Express.

SQLPad是一個基于Nodejs開發的直接在瀏覽器運行SQL查詢并對結果進行可視化展示工具。SQLPad支持的數據庫非常多，比如：MySQL, Postgres, SQL Server, Vertica, Crate, Presto等。

使用kubectl get services拿到sqlpad的external IP：

在瀏覽器里輸入剛才獲得的IP地址，后面加上默認的3000端口，打開sqlpad的web控制臺：

注冊一個帳戶并登錄：

選擇admin-Connections：

新建一個數據庫連接：

database driver從下拉菜單里選擇SAP HANA：

回到Google Cloud Platform的cloud shell，使用kubectl get services獲得hxe-connect的external IP：

把這個地址填到數據庫創建向導里：

創建一個名為quotes的collection并插入一些數據：

create collection quotes;insert into quotes values ( { "FROM" : 'HOMER', "TO" : 'BART', "QUOTE" : 'I want to share something with you: The three little sentences that will get you through life. Number 1: Cover for me. Number 2: Oh, good idea, Boss! Number 3: It wai like that when I got here.', "MOES_BAR" : 'Point( -86.880306 36.508361 )', "QUOTE_ID" : 1 });insert into quotes values ( { "EPISODE" : 'GRADE SCHOOL CONFIDENTIAL', "FROM" : 'HOMER', "QUOTE" : 'Wait a minute. Bart''s teacher is named Krabappel? Oh, I''ve been calling her Crandall. Why did not anyone tell me? Ohhh, I have been making an idiot out of myself!', "QUOTE_ID" : 2, "MOES_BAR" : 'Point( 2.161018 41.392641 )' });insert into quotes values ( { "FROM" : 'HOMER', "QUOTE" : 'Oh no! What have I done? I smashed open my little boy''s piggy bank, and for what? A few measly cents, not even enough to buy one beer. Weit a minute, lemme count and make sure…not even close.', "MOES_BAR" : 'Point( -122.400690 37.784366 )', "QUOTE_ID" : 3 });

注意這個生成的sql collection并不是數據庫表，而是一種document store(noSQL)，實際上只是鍵值對-key value pair.

下面的SQL語句執行的操作是把document store里的值取出進行分析，將分析結果存放到新創建的column table里：

--Create a columnar table with a text fuzzy search index create column table quote_analysis (id integer,homer_quote text FAST PREPROCESS ON FUZZY SEARCH INDEX ON,lon_lat nvarchar(200));-- Copy the quotes form the JSON store to the relational table insert into quote_analysis with doc_store as (select quote_id, quote from quotes) select doc_store.quote_id as id, doc_store.quote as homer_quote, 'Point( 2.151255 41.354159 )' from doc_store;

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