database

Below the interested part of code using spring xml <bean id="ds-patriot-dw_ro" class="org.springframework.jdbc.datasource.DriverManagerDataSource"> <property name="driverClassName" value="oracle.jdbc.OracleDriver" /> <property name="url" value="jdbc:oracle:thin:@//patriot.redaelli.org:1111/RED"/> <property name="Username" value="user"/> <property name="Password" value="pwd"/> </bean> <camelContext id="MyCamel" streamCache="true" xmlns="http://camel.apache.org/schema/spring"> <route id="scheduler"> <from uri="timer:hello?repeatCount=1"/> <setHeader headerName="ndays"> <constant>0</constant> </setHeader> <to uri="direct:start"/> </route> <route> <from uri="direct:start"/> <setBody> <constant>table1,table2,table3</constant> </setBody> <split streaming="true"> <tokenize token="," /> <setHeader headerName="tablename"> <simple>${body}</simple> </setHeader> <to uri="direct:jdbc2csv"/> </split> </route> <route> <from uri="direct:jdbc2csv"/> <to uri="direct:get-jdbc-data" pattern="InOut" /> <to uri="direct:export-csv" /> </route> <route> <from uri="direct:get-jdbc-data"/> <log message="quering table ${headers....

You can query public knowledge graph databases (like wikidata.org and dbpedia.org) using SPARQL. For instance for extracting all “known” programming languages, you can use the query SELECT ?item ?itemLabel WHERE { ?item wdt:P31 wd:Q9143. SERVICE wikibase:label { bd:serviceParam wikibase:language "[AUTO\_LANGUAGE],en". } } LIMIT 1000 There are also SPARQL clients for most of programming languages. With (swi) prolog you can easily run \[library(semweb/sparql\_client)\]. sparql\_query('SELECT ?item ?itemLabel WHERE {?item wdt:P31 wd:Q9143. SERVICE wikibase:label { bd:serviceParam wikibase:language "\[AUTO\_LANGUAGE\],en"....

I have started learning node.js: The first result is this github repository where you can find a basic project of a rest web service that exposes oracle data. How to run the service forever (with autorestart on failures)? I tested it both with a docker container and the pm2 tool

Using Apache spark 2.0 and python I’ll show how to import a table from a relational database (using its jdbc driver) into a python dataframe and save it in a parquet file. In this demo the database is an oracle 12.x file jdbc-to-parquet.py:``` from pyspark.sql import SparkSession spark = SparkSession \ .builder \ .appName(“Python Spark SQL basic example”) \ .getOrCreate() df = spark.read.format(“jdbc”).options(url=“jdbc:oracle:thin:ro/ro@mydboracle.redaelli.org:1521:MYSID”, dbtable=“myuser.dim_country”, driver=“oracle.jdbc.OracleDriver”).load() df.write.parquet(“country.parquet”)

This is fast tutorial of using the Caylay graph database (with MongoDB as backend): Cayley is “not a Google project, but created and maintained by a Googler, with permission from and assignment to Google, under the Apache License, version 2.0” download and unzip a binary distribution edit cayley.cfg { "database": "mongo", "db\_path": "cayley.redaelli.org:27017", "read\_only": false, "host": "0.0.0.0" } ./cayley init -config=cayley.cfg ./cayley http -config=cayley.cfg -host=“0.0.0.0” & create a file demo....