Using SQLite with the Android emulator and Eclipse

One of the ways of persisting data with Android is to use a SQLite database. A fuller list of methods is given here. When you are persisting data in any application one of the things you will want to do is write ad hoc queries to see is you data getting to the database, how big are your tables etc. SQLLite lets you do this with the databases that your applications use in the emulator. You will need to connect to the emulator using the Android Debug Bridge (adb). Type this at a command prompt (you obviously need to have adb.exe on your path, or just open a command prompt in the tools directory of your android installation - \android-sdk-windows\tools in my case):


adb -s emulator-5554 shell

The name of your emulator may be different, you can check the name in the console of eclipse when you are launching an app to run on the emulator.
Once you have run that you will need to use the sqlite3 command to mount the database you are interested in. Enter this at the shell prompt which you just opened:

sqlite3 path_to_your_db_file

To find out what that path is open the DDMS perspective in eclipse. There is a file explorer tab. Under this there will be a folder called data. This contains another folder called data which in turn contains a folder named after the package name that you used setting up your project. In my case com.nolantech. Inside that is another folder called databases and finally the file you are interested. The file name is the one you will have assigned in code when you first opened the database. So for me that is all:

sqlite3 /data/data/com.nolantech/databases/data

You are then able to examine your tables (enter .tables for a list) using normal SQL syntax.
Note that any commands that you enter here which are preceded by a . are SQLite commands. They are run by the shell. Any other commands are database commands and are passed from the shell to the underlying database library for handling.
Type .help for a fuller list of what you can do.

Comments

Post a Comment

Popular posts from this blog

AutoCompleteTextView backed with data from SQLite in Android

Image
This is a handy piece of code. As your database gets bigger you can allow the user to pick the correct value by typing. If the db gets very big, you can always increase the threshold, so that the query does not run until there will be a suitably sized resultset returned. Running it at a threshold of 1 is fine for very small resultsets.  Here is the code you need to back your AutoCompleteTextView with a cursor adapter. @Override protected void onResume() { super.onResume(); text = (AutoCompleteTextView) findViewById(R.id.autoCompleteTextView1); final AdapterHelper h = new AdapterHelper(this); Cursor c = h.getAllResults(); startManagingCursor(c); String[] from = new String[] { "val" }; int[] to = new int[] { android.R.id.text1 }; CursorAdapter adapter = new MyCursorAdapter(this, android.R.layout.simple_dropdown_item_1line, c, from, to); adapter.setFilterQueryProvider(new FilterQueryProvider() { public Cursor runQuery(Cha
Read more

Building a choropleth map for Irish agricultural data

I wanted to create a choropleth map  using Irish data. The Irish Government has made a large quantity of data available at data.gov.ie. The set I chose was for Bovine TB across Ireland over a number of years. You can get geojson for a variety of countries and Ireland's county boundaries are available. All I had to do was get the data labels to match. In the data some counties are split into 2 parts. I merged and summed these data points to get the choropleth to work with normal county boundaries. You can see the results here . A link to the github is included at the top of the notebook.
Read more

Using Statistics to Hire Developers

The Interview I was interviewing a developer for a mid level position today and he turned out to be not up to scratch. The CV looked pretty good, but when I dug in with some fundamental Java questions he was found wanting. Not an unusual occurrence, but still costly. It took 30 minutes of my time, his time and a number of other people were involved to get the process to this stage. I wondered if there might be a way to remove some of the candidate CVs from the batch before we do the costly part of interviewing. Spam or Ham Classifying CVs could be considered like the Spam/Ham problem. Apache SpamAssassin is a good example of a spam classifier. It can probably be made to classify CVs - or at least try, but it is written in C, I think and that is not my thing any more. This looks interesting, so I forked it, converted it to eclipse and started the process of making it build with Maven. First I am going to try this out with spam and ham email, then will try it for other text p
Read more