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diff --git a/.idea/gtfs-book/ch-13-importing-to-sql.md b/.idea/gtfs-book/ch-13-importing-to-sql.md new file mode 100644 index 0000000..e96517c --- /dev/null +++ b/.idea/gtfs-book/ch-13-importing-to-sql.md @@ -0,0 +1,125 @@ +## 13. Importing a GTFS Feed to SQL + +One of the great things about GTFS is that it is already in a format +conducive to being used in an SQL database. The presence of various IDs +in each of the different files makes it easy to join the tables in order +to extract the data you require. + +To try this yourself, download `GtfsToSql` +(<https://github.com/OpenMobilityData/GtfsToSql>). This is a Java +command-line application that imports a GTFS feed to an SQLite database. +This application also supports PostgreSQL, but the examples used here +are for SQLite. + +The pre-compiled `GtfsToSql` Java archive can be downloaded from its +GitHub repository at +<https://github.com/OpenMobilityData/GtfsToSql/tree/master/dist>. + +To use `GtfsToSql`, all you need is an extracted GTFS feed. The +following instructions demonstrate how you to import the TriMet feed +that has been referenced throughout this book. + +Firstly, download and extract the feed. The following commands use curl +to download the file, then unzip to extract the file to a sub-directory +called `trimet`. + +``` +$ curl http://developer.trimet.org/schedule/gtfs.zip > gtfs.zip + +$ unzip gtfs.zip -d trimet/ +``` + +To create an SQLite database from this feed, the following command can +be used. + +``` +$ java -jar GtfsToSql.jar -s jdbc:sqlite:./db.sqlite -g ./trimet +``` + +This may take a minute or two to complete (you will see progress as it +imports the feed and then creates indexes), and at the end you will have +a GTFS database in a file called `db.sqlite`. You can then query this +database with the command-line `sqlite3` tool, as shown in the +following example. + +``` +$ sqlite3 db.sqlite +sqlite> SELECT * FROM agency; +|TriMet|http://trimet.org|America/Los_Angeles|en|503-238-7433 + +sqlite> SELECT * FROM routes WHERE route_type = 0; +90|||MAX Red Line||0|http://trimet.org/schedules/r090.htm|| +100|||MAX Blue Line||0|http://trimet.org/schedules/r100.htm|| +190|||MAX Yellow Line||0|http://trimet.org/schedules/r190.htm|| +193||Portland Streetcar|NS Line||0|http://trimet.org/schedules/r193.htm|| +194||Portland Streetcar|CL Line||0|http://trimet.org/schedules/r194.htm|| +200|||MAX Green Line||0|http://trimet.org/schedules/r200.htm|| +250|||Vintage Trolley||0|http://trimet.org/schedules/r250.htm|| +``` + +The first query above finds all agencies stored in the database, while +the second finds all routes marked as Light Rail (`route_type` of +`0`). + +**Note: In the following chapters there are more SQL examples. All of +these examples are geared towards running on an SQLite database that has +been created in this manner.** + +All tables in this database match up with the corresponding GTFS +filename (so for `agency.txt`, the table name is `agency`, while for +`stop_times.txt` the table name is `stop_times`). The columns in SQL +have the same name as the value in the corresponding GTFS file. + +***Note:** All data imported using this tool is stored as text in the +database. This means you may need to be careful when querying integer +data. For example, ordering stop times by stop_sequence may not produce +expected results (for instance, 29 as a string comes before 3). Although +it is a performance hit, you can change this behavior by casting the +value to integer, such as: ORDER BY stop_sequence + 0. The reason +`GtfsToSql` works in this way is because it is intended as a lightweight +tool to be able to quickly query GTFS data. I recommend rolling your own +importer to treat data exactly as you need it, especially in conjunction +with some of the optimization techniques recommended later in this book.* + +### File Encodings + +The GTFS specification does not indicate whether files should be encoded +using UTF-8, ISO-8859-1 or otherwise. Since a GTFS feed is not +necessarily in English, you must be willing to handle an extended +character set. + +The GtfsToSql tool introduced above automatically detects the encoding +of each file using the juniversalchardet Java library +(<https://code.google.com/p/juniversalchardet/>). + +I recommend you take some time looking at the source code of GtfsToSql +to further understand this so you are aware of handling encodings +correctly if you write your own parser. + +### Optimizing GTFS Feeds + +If you are creating a database that is to be distributed onto a mobile +device such as an iPhone or Android phone, then disk space and +computational power is at a premium. Even if you are setting up a +database to be queried on a server only, then making the database +perform as quickly as possible is still important. + +In the following chapters are techniques for optimizing GTFS feeds. +There are many techniques that can be applied to improve the performance +of GTFS, such as: + +* Using integer identifiers rather than string identifiers (for route + IDs, trip IDs, stop IDs, etc.) and creating appropriate indexes +* Removing redundant shape points and encoding shapes +* Deleting unused data +* Reusing repeating trip patterns. + +Changing the data to use integer IDs makes the greatest improvement to +performance, but the other techniques also help significantly. + +Depending on your needs, there are other optimizations that can be made +to reduce file size and speed up querying of the data, but the ease of +implementing them may depend on your database storage system and the +programming language used to query the data. The above list is a good +starting point. + |