README.md

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P3 Wrangle Data

Udacity Data analyst Training

Marcus Pauli | p3 Wrangle Data | 26.02.2017

Reviewer notes:

As the project did not state out to use an explicit technology, I did all that with a virtual Ubuntu version. How to accomplish the whole task with the Anaconda/Notebook looked far too complicated and would have needed even more time to accomplish.

Thus I did it with below mentioned tools and the additions within the appendix to accomplish the actual SQL statements and results to get the results to complete the project.

The SQL statements are written down within this document.

The actual SQL-DB is uploaded to the GitHUB as ZIP file.

Target 1: Choose Your Map Area

Choose any area of the world from https://www.openstreetmap.org, and download a XML OSM dataset. The dataset should be at least 50MB in size (uncompressed). We recommend using one of following methods of downloading a dataset:

·            Download a preselected metro area from Map Zen.

·            Use the Overpass API to download a custom square area.

Explanation of the syntax can found in the wiki. In general you will want to use the following query:(node(minimum_latitude, minimum_longitude, maximum_latitude, maximum_longitude);<;);out meta; e.g. (node(51.249,7.148,51.251,7.152);<;);out meta; the meta option is included so the elements contain timestamp and user information. You can use the Open Street Map Export Tool to find the coordinates of your bounding box. Note: You will not be able to use the Export Tool to actually download the data, the area required for this project is too large.

Solution:

The Area of southern Bavaria in Germany was chosen as data source and the data was

downloaded accordingly from: http://download.geofabrik.de/europe/germany/bayern/oberbayern-latest.osm.bz2

 

 

Target 2: Process your Dataset

It is recommended that you start with the problem sets in your chosen course and modify them to suit your chosen data set. As you unravel the data, take note of problems encountered along the way as well as issues with the dataset. You are going to need these when you write your project report.

SQL

Thoroughly audit and clean your dataset, converting it from XML to CSV format. Then import the cleaned .csv files into a SQL database using this schema or a custom schema of your choice.

Solution

With postgresql and PostGIS

Prepare postgres for the data

sudo -u postgres -i

createuser gis

createdb -E UTF8 -O gis gis

psql -f /usr/share/postgresql/9.3/contrib/postgis-2.1/postgis.sql -d gis

psql -f /usr/share/postgresql/9.3/contrib/postgis-2.1/spatial_ref_sys.sql -d gis

psql -f /usr/share/postgresql/9.3/contrib/postgis-2.1/postgis_comments.sql -d gis

 

echo "alter table geometry_columns owner to gis; alter table spatial_ref_sys owner to gis;" | psql -d gis

echo "create extension hstore;" | psql -d gis

 

Get the raw data:

 

Get OpenStreet data for my region of Germany:

Wget http://download.geofabrik.de/europe/germany/bayern/oberbayern-latest.osm.bz2

 

Import the raw data:

osm2pgsql -c -d gis -C 2048 --hstore --slim /home/mpauli/P3_Data_Wrangle/oberbayern-latest.osm.bz2

è node cache: stored: 13663936(100.00%), storage efficiency: 50.82% (dense blocks: 1387, sparse nodes: 12734263), hit rate: 100.00%

13663936 Nodes imported from the datafile of southern Bavaria.

 

Postactions on the postgres to enhance performance (creating indices)

sudo -u postgres -i psql gis

CREATE INDEX idx_planet_osm_point_tags ON planet_osm_point USING gist(tags);

CREATE INDEX idx_planet_osm_polygon_tags ON planet_osm_polygon USING gist(tags);

CREATE INDEX idx_planet_osm_line_tags ON planet_osm_line USING gist(tags);

\q

 

Answering Questions on the datasource:

Find restaurants within southern bavaria:

SELECT name, ST_AsText(ST_Transform(way,4326)) AS pt_lonlattext

FROM planet_osm_point

WHERE amenity='restaurant';

gis=# SELECT name, ST_AsText(ST_Transform(way,4326)) AS pt_lonlattext

gis-# FROM planet_osm_point

gis-# WHERE amenity='restaurant';

                                  name                                    |              pt_lonlattext

-------------------------------------------------------------------------+------------------------------------------

 Gletschergarten                                                   | POINT(10.9795116856019 47.4131929633555)

 Gletscherrestaurant SonnAlpin                          | POINT(10.9799992013066 47.4133826872785)

 Panorama Gipfelrestaurant                                | POINT(10.9840178147301 47.4213887055371)

 Knorrhütte                                                            | POINT(11.0127748632684 47.4100231779253)

 Reintalangerhütte                                               | POINT(11.0356812741927 47.4053133154913)

 Eibsee-Alm                                                            | POINT(10.9928391809886 47.4546240801471)

 Restaurant Alpspitze                                           | POINT(11.0510024006895 47.4391943885217)

 Höllentaleingangshütte                                       | POINT(11.0444883572382 47.4483891182407)

 Kreuzjochhaus                                                      | POINT(11.0734764524676 47.4515120675542)

 Bockhütte                                                             | POINT(11.0943020956994 47.4181706040471)

                                                                               | POINT(11.1130838021651 47.4193425032333)

 Lisa Hütte                                                             | POINT(11.0860896973719 47.4430368647164)

 Wettersteinalm                                                    | POINT(11.1442002757972 47.4297560035039)

 Lautersee Stub'n                                                   | POINT(11.2324476252056 47.4381316931787)

Results were truncated …

 

Find restaurants serving pizza within southern bavaria:

SELECT name, ST_AsText(ST_Transform(way,4326)) AS pt_lonlattext

FROM planet_osm_point

WHERE amenity='restaurant' AND tags @> 'cuisine=>pizza';

 

 

                name                |              pt_lonlattext

------------------------------------+------------------------------------------

 Angelina's Pizza-Heim-Service      | POINT(10.8846801343185 47.8113651190073)

 Colosseo                           | POINT(11.0901564604947 47.492625918016)

 Ristorante da Noi                  | POINT(11.2003933104169 47.6773875120891)

 Ristorante Pizzeria Galeria        | POINT(10.8007638323895 48.069122202831)

 Grillos Holzofenpizza              | POINT(10.874744228287 48.0515311634334)

 Antica Roma                        | POINT(10.8848790213224 48.0460879780449)

 Landhaus                           | POINT(11.1264243231235 47.8301202705061)

 Bella Italia                       | POINT(11.1463494052829 47.8449419612061)

 Pizzeria Da Pietro                 | POINT(11.1000289454671 47.9472109690419)

 Sportheim                          | POINT(10.9336016660395 48.0664203116721)

 Ristorante Pizzeria Mediterraneo   | POINT(11.2481527814863 48.0744285037287)

 Pizzeria Vier Jahreszeiten         | POINT(11.1856463870498 48.8925111688232)

 Da Alfonso                         | POINT(11.3144232966264 47.6555265713339)

 El Lago                            | POINT(11.8654722599559 47.7330864638232)

 La Locanda Locanda                 | POINT(12.1855551110908 47.6116677888042)

 Tropea Da Bobby                    | POINT(12.1878468930436 47.6099318651742)

 

Results were truncated …

 

Find restaurants in Ottobrunn (my hometown):

 

SELECT name, tags, ST_AsText(ST_Transform(way,4326)) AS pt_lonlattext

FROM planet_osm_point

WHERE tags @> 'addr:city=>Ottobrunn';

 

gis=# SELECT name, ST_AsText(ST_Transform(way,4326)) AS pt_lonlattext

FROM planet_osm_point

WHERE amenity='restaurant' AND tags @> 'addr:city=>Ottobrunn';

               name                |              pt_lonlattext

-----------------------------------+------------------------------------------

 Nefeli im Phönix                  | POINT(11.6523698658383 48.0569127702025)

 Asia Garden                       | POINT(11.6646628613438 48.0593236676815)

 Giannis                           | POINT(11.6642053493696 48.0595751140524)

 Asahi                             | POINT(11.6662243129706 48.0587087956779)

 Taj Palace                        | POINT(11.6673393019013 48.0594653015453)

 Das Nimrods                       | POINT(11.6639590313187 48.0614998869332)

 Chop Stick - Running Sushi        | POINT(11.6624574973213 48.062809464647)

 Villa Meraviglia                  | POINT(11.6623044243969 48.0642946690474)

 Happy Quynh                       | POINT(11.6627057018343 48.0639727052979)

 Bistro Luigi Enoteca & Ristorante | POINT(11.6635988967213 48.0645567171164)

 Vu Garden                         | POINT(11.6641324061685 48.0648421768968)

 Quo Vadis                         | POINT(11.6641951984069 48.0647619121301)

 Ayinger Alm                       | POINT(11.6652234999126 48.0649007094637)

 Das Wirtshaus am Rathausplatz     | POINT(11.6655286576146 48.0650581767467)

 Bella Roma                        | POINT(11.6585540479172 48.0679117150216)

 Taverna Artemis                   | POINT(11.6568928832938 48.0706521850695)

 Ristorante Pattio D'oro           | POINT(11.6625857767438 48.0655903681733)

 VINO e CUCINA                     | POINT(11.6641748964815 48.0666143934543)

 Ristorante Cristalina             | POINT(11.6662887221765 48.0655047016339)

 Nissos                            | POINT(11.6782292187646 48.0624766850937)

 ottofonti                         | POINT(11.6788494156367 48.0625453064189)

 Maharani                          | POINT(11.668440187282 48.0673745650675)

 Trattoria Portofino               | POINT(11.6770623072105 48.069298205928)

 Balkan Grill                      | POINT(11.6895553575298 48.0660005090129)

 da Bruno                          | POINT(11.6917742861131 48.0726922707044)

 

Who has committed the most data?

SELECT user, COUNT(*) FROM open_street.nodes

GROUP BY user

;

ToniE	271359
rolandg	53268
Rainero	24353
ludwich	19676

Target 3: Explore your Database

After building your local database you’ll explore your data by running queries. Make sure to document these queries and their results in the submission document described below. See the Project Rubric for more information about query expectations.

 

Solution:

 

Below is the converted table structure of the PostgresDB:

 

PostgreSQL Tables:

 

 

The actual raw data of openstreet has the below structure/schema:

 

 

 

 

Target 4: Document your Work

Create a document (pdf, html) that directly addresses the following sections from the Project Rubric.

 

·                 Problems encountered in your map

·                 Overview of the Data

·                 Other ideas about the datasets

Try to include snippets of code and problematic tags (see MongoDB Sample Project or SQL Sample Project) and visualizations in your report if they are applicable.

Use the following code to take a systematic sample of elements from your original OSM region. Try changing the value of k so that your resulting SAMPLE_FILE ends up at different sizes. When starting out, try using a larger k, then move on to an intermediate k before processing your whole dataset.

 

Solution:

This document is my documentation, the data is been held within this document. The source data was far too big for GitHUB.

 

Appendix:

Information sources:

http://craigthomas.ca/blog/category/openstreetmap/

http://www.mysqltutorial.org/mysql-subquery/

https://de.slideshare.net/jynus/query-optimization-with-mysql-57-and-mariadb-10-even-newer-tricks

http://wiki.openstreetmap.org/wiki/User:Tagtheworld

http://goblor.de/wp/2009/10/16/openstreetmap-projekt-teil-1-openstreetmap-daten-in-mysql-datenbank-einlesen/

mysqldump.exe --defaults-file="c:\users\mpauli~1.ccs\appdata\local\temp\tmpetkjmq.cnf"  --user=root --host=127.0.0.1 --protocol=tcp --port=3306 --default-character-set=utf8 --routines --skip-triggers "open_street"

 

https://review.udacity.com/#!/rubrics/25/view

Create DB for

postgres=# create extension hstore;

-- Database creation script for the snapshot PostgreSQL schema.
	-- Drop all tables if they exist.
	DROP TABLE IF EXISTS actions;
	DROP TABLE IF EXISTS users;
	DROP TABLE IF EXISTS nodes;
	DROP TABLE IF EXISTS ways;
	DROP TABLE IF EXISTS way_nodes;
	DROP TABLE IF EXISTS relations;
	DROP TABLE IF EXISTS relation_members;
	DROP TABLE IF EXISTS schema_info;
	-- Drop all stored procedures if they exist.
	DROP FUNCTION IF EXISTS osmosisUpdate();
	-- Create a table which will contain a single row defining the current schema version.
	CREATE TABLE schema_info (
	version integer NOT NULL
	);
	-- Create a table for users.
	CREATE TABLE users (
	id int NOT NULL,
	name text NOT NULL
	);
	-- Create a table for nodes.
	CREATE TABLE nodes (
	id bigint NOT NULL,
	version int NOT NULL,
	user_id int NOT NULL,
	tstamp timestamp without time zone NOT NULL,
	changeset_id bigint NOT NULL,
	tags hstore
	);
	-- Add a postgis point column holding the location of the node.
	SELECT AddGeometryColumn('nodes', 'geom', 4326, 'POINT', 2);
	-- Create a table for ways.
	CREATE TABLE ways (
	id bigint NOT NULL,
	version int NOT NULL,
	user_id int NOT NULL,
	tstamp timestamp without time zone NOT NULL,
	changeset_id bigint NOT NULL,
	tags hstore,
	nodes bigint[]
	);
	-- Create a table for representing way to node relationships.
	CREATE TABLE way_nodes (
	way_id bigint NOT NULL,
	node_id bigint NOT NULL,
	sequence_id int NOT NULL
	);
	-- Create a table for relations.
	CREATE TABLE relations (
	id bigint NOT NULL,
	version int NOT NULL,
	user_id int NOT NULL,
	tstamp timestamp without time zone NOT NULL,
	changeset_id bigint NOT NULL,
	tags hstore
	);
	-- Create a table for representing relation member relationships.
	CREATE TABLE relation_members (
	relation_id bigint NOT NULL,
	member_id bigint NOT NULL,
	member_type character(1) NOT NULL,
	member_role text NOT NULL,
	sequence_id int NOT NULL
	);
	-- Configure the schema version.
	INSERT INTO schema_info (version) VALUES (6);
	-- Add primary keys to tables.
	ALTER TABLE ONLY schema_info ADD CONSTRAINT pk_schema_info PRIMARY KEY (version);
	ALTER TABLE ONLY users ADD CONSTRAINT pk_users PRIMARY KEY (id);
	ALTER TABLE ONLY nodes ADD CONSTRAINT pk_nodes PRIMARY KEY (id);
	ALTER TABLE ONLY ways ADD CONSTRAINT pk_ways PRIMARY KEY (id);
	ALTER TABLE ONLY way_nodes ADD CONSTRAINT pk_way_nodes PRIMARY KEY (way_id, sequence_id);
	ALTER TABLE ONLY relations ADD CONSTRAINT pk_relations PRIMARY KEY (id);
	ALTER TABLE ONLY relation_members ADD CONSTRAINT pk_relation_members PRIMARY KEY (relation_id, sequence_id);
	-- Add indexes to tables.
	CREATE INDEX idx_nodes_geom ON nodes USING gist (geom);
	CREATE INDEX idx_way_nodes_node_id ON way_nodes USING btree (node_id);
	CREATE INDEX idx_relation_members_member_id_and_type ON relation_members USING btree (member_id, member_type);
	-- Set to cluster nodes by geographical location.
	ALTER TABLE ONLY nodes CLUSTER ON idx_nodes_geom;
	-- Set to cluster the tables showing relationship by parent ID and sequence
	ALTER TABLE ONLY way_nodes CLUSTER ON pk_way_nodes;
	ALTER TABLE ONLY relation_members CLUSTER ON pk_relation_members;
	-- There are no sensible CLUSTER orders for users or relations.
	-- Depending on geometry columns different clustings of ways may be desired.
	-- Create the function that provides "unnest" functionality while remaining compatible with 8.3.
	CREATE OR REPLACE FUNCTION unnest_bbox_way_nodes() RETURNS void AS $$
	DECLARE
	previousId ways.id%TYPE;
	currentId ways.id%TYPE;
	result bigint[];
	wayNodeRow way_nodes%ROWTYPE;
	wayNodes ways.nodes%TYPE;
	BEGIN
	FOR wayNodes IN SELECT bw.nodes FROM bbox_ways bw LOOP
	FOR i IN 1 .. array_upper(wayNodes, 1) LOOP
	INSERT INTO bbox_way_nodes (id) VALUES (wayNodes[i]);
	END LOOP;
	END LOOP;
	END;
	$$ LANGUAGE plpgsql;
	-- Create customisable hook function that is called within the replication update transaction.
	CREATE FUNCTION osmosisUpdate() RETURNS void AS $$
	DECLARE
	BEGIN
	END;
	$$ LANGUAGE plpgsql;
	-- Manually set statistics for the way_nodes and relation_members table
	-- Postgres gets horrible counts of distinct values by sampling random pages
	-- and can be off by an 1-2 orders of magnitude
	-- Size of the ways table / size of the way_nodes table
	ALTER TABLE way_nodes ALTER COLUMN way_id SET (n_distinct = -0.08);
	-- Size of the nodes table / size of the way_nodes table * 0.998
	-- 0.998 is a factor for nodes not in ways
	ALTER TABLE way_nodes ALTER COLUMN node_id SET (n_distinct = -0.83);
	-- API allows a maximum of 2000 nodes/way. Unlikely to impact query plans.
	ALTER TABLE way_nodes ALTER COLUMN sequence_id SET (n_distinct = 2000);
	-- Size of the relations table / size of the relation_members table
	ALTER TABLE relation_members ALTER COLUMN relation_id SET (n_distinct = -0.09);
	-- Based on June 2013 data
	ALTER TABLE relation_members ALTER COLUMN member_id SET (n_distinct = -0.62);
	-- Based on June 2013 data. Unlikely to impact query plans.
	ALTER TABLE relation_members ALTER COLUMN member_role SET (n_distinct = 6500);
	-- Based on June 2013 data. Unlikely to impact query plans.
	ALTER TABLE relation_members ALTER COLUMN sequence_id SET (n_distinct = 10000);

 

Working MySQL Version f the schema:

SET SQL_MODE="NO_AUTO_VALUE_ON_ZERO";

 

--

-- Datenbank: `osm`

--

 

-- --------------------------------------------------------

 

--

-- Tabellenstruktur für Tabelle `member_node`

--

 

CREATE TABLE `member_node` (

  `nodeid` int(11) NOT NULL,

  `relid` int(11) NOT NULL,

  `role` varchar(255) NOT NULL,

  KEY `wayid` (`nodeid`,`relid`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

 

-- --------------------------------------------------------

 

--

-- Tabellenstruktur für Tabelle `member_relation`

--

 

CREATE TABLE `member_relation` (

  `relid2` int(11) NOT NULL,

  `relid` int(11) NOT NULL,

  `role` varchar(255) NOT NULL,

  KEY `wayid` (`relid2`,`relid`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

 

-- --------------------------------------------------------

 

--

-- Tabellenstruktur für Tabelle `member_way`

--

 

CREATE TABLE `member_way` (

  `wayid` int(11) NOT NULL,

  `relid` int(11) NOT NULL,

  `role` varchar(255) default NULL,

  KEY `wayid` (`wayid`,`relid`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

 

-- --------------------------------------------------------

 

--

-- Tabellenstruktur für Tabelle `nodes`

--

 

CREATE TABLE `nodes` (

  `id` int(11) NOT NULL,

  `lat` double NOT NULL,

  `lon` double NOT NULL,

  `visible` tinyint(1) default NULL,

  `user` char(50) default NULL,

  `timestamp` datetime default NULL,

  PRIMARY KEY  (`id`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

 

-- --------------------------------------------------------

 

--

-- Tabellenstruktur für Tabelle `node_tags`

--

 

CREATE TABLE `node_tags` (

  `id` int(11) NOT NULL,

  `k` varchar(50) NOT NULL,

  `v` varchar(255) NOT NULL,

  KEY `id` (`id`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

 

-- --------------------------------------------------------

 

--

-- Tabellenstruktur für Tabelle `relations`

--

 

CREATE TABLE `relations` (

  `id` int(11) NOT NULL,

  `visible` tinyint(4) default NULL,

  `user` varchar(50) default NULL,

  `timestamp` datetime default NULL,

  PRIMARY KEY  (`id`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

 

-- --------------------------------------------------------

 

--

-- Tabellenstruktur für Tabelle `relation_tags`

--

 

CREATE TABLE `relation_tags` (

  `id` int(11) NOT NULL,

  `k` varchar(50) NOT NULL,

  `v` varchar(255) NOT NULL,

  KEY `id` (`id`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

 

-- --------------------------------------------------------

 

--

-- Tabellenstruktur für Tabelle `ways`

--

 

CREATE TABLE `ways` (

  `id` int(11) NOT NULL,

  `visible` tinyint(4) default NULL,

  `user` varchar(50) default NULL,

  `timestamp` datetime default NULL,

  PRIMARY KEY  (`id`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

 

-- --------------------------------------------------------

 

--

-- Tabellenstruktur für Tabelle `ways_nodes`

--

 

CREATE TABLE `ways_nodes` (

  `nodeid` int(11) NOT NULL,

  `wayid` int(11) NOT NULL,

  `sequence` int(11) NOT NULL,

  KEY `nodeid` (`nodeid`,`wayid`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

 

-- --------------------------------------------------------

 

--

-- Tabellenstruktur für Tabelle `way_tags`

--

 

CREATE TABLE `way_tags` (

  `id` int(11) NOT NULL,

  `k` varchar(50) NOT NULL,

  `v` varchar(255) NOT NULL,

  KEY `id` (`id`)

) ENGINE=InnoDB DEFAULT CHARSET=utf8;

{:/}