Parsing Bitcoin Blockchain Data in Java
posted at June 27, 2014 with tags bitcoin, java

Last week I spent some time on collecting certain statistics (e.g., average number of performed transactions and created blocks per month) over a vast (~20GB) Bitcoin blockchain dataset. The hardest part for me was to pick the right tool to parse the raw blockchain data. First, I hit the Google with “parse bitcoin blockchain” keywords. Unfortunately, the returned results (bitcointools, blockchain, blockparser, etc.) point to almost undocumented projects, where some appear to not even work. (As a side note, bitcointools require a running BitcoinQt/bitcoind process in the background, which I find pretty amusing.) Next, I checked some papers on Google Scholars to find out how other people solved the problem. A paper leaded me to BitcoinArmory project, which requires a dozen of manual interventions to get installed. (I did not even attempt to install it.) Suddenly, it occured me to add a “java” keyword to the search phrase, which led me to bitcoinj project. bitcoinj is far most the best Bitcoin blockchain parser library that I have ever met. It has a rich documentation, developer-friendly (and fully documented) API and works out of the box. It is composed of a single JAR, no other requirements, stupid hassles, etc. In addition, its IRC channel at FreeNode is packed with real people that provide instant support on any Bitcoin related questions.

Enough with the talk! Let’s get our hands dirty with the code. I first included the bitcoinj Maven dependency in my pom.xml as follows:


Next, I downloaded a couple of raw blockchain data for test purposes:

Here comes the simplest part: the Java code. Below, I calculate the average number of transactions per block per month.


import java.util.ArrayList;  
import java.util.HashMap;
import java.util.List;
import java.util.Map;

// Arm the blockchain file loader.
NetworkParameters np = new MainNetParams();
List<File> blockChainFiles = new ArrayList<>();
blockChainFiles.add(new File("/tmp/bootstrap.dat"));
BlockFileLoader bfl = new BlockFileLoader(np, blockChainFiles);

// Data structures to keep the statistics.
Map<String, Integer> monthlyTxCount = new HashMap<>();
Map<String, Integer> monthlyBlockCount = new HashMap<>();

// Iterate over the blocks in the dataset.
for (Block block : bfl) {

    // Extract the month keyword.
    String month = new SimpleDateFormat("yyyy-MM").format(block.getTime());

    // Make sure there exists an entry for the extracted month.
    if (!monthlyBlockCount.containsKey(month)) {
        monthlyBlockCount.put(month, 0);
        monthlyTxCount.put(month, 0);

    // Update the statistics.
    monthlyBlockCount.put(month, 1 + monthlyBlockCount.get(month));
    monthlyTxCount.put(month, block.getTransactions().size() + monthlyTxCount.get(month));


// Compute the average number of transactions per block per month.
Map<String, Float> monthlyAvgTxCountPerBlock = new HashMap<>();
for (String month : monthlyBlockCount.keySet())
            month, (float) monthlyTxCount.get(month) / monthlyBlockCount.get(month));

That’s it! In order to appreciate the hassle-free simplicity of the bitcoinj interface, you ought to take your time and spend a couple of hours on other tools first. (About the performance, for the sample blockchain dataset of size 4.7 GB, above code snippet completes in less than 2 minutes on my 2.4 GHz GNU/Linux notebook without any JVM flags. Pretty zippy!)