JAVA - Best approach to parse huge (extra large) JSON file

Question

I'm trying to parse some huge JSON file (like http://eu.battle.net/auction-data/258993a3c6b974ef3e6f22ea6f822720/auctions.json) using gson library (http://code.google.com/p/google-gson/) in JAVA.

I would like to know what is the best approch to parse this kind of big file (about 80k lines) and if you may know good API that can help me processing this.

Some idea...

1. read line by line and get rid of the JSON format: but that's nonsense.
2. reduce the JSON file by splitting this file into many other: but I did not find any good Java API for this.
3. use this file directlly as nonSql database, keep the file and use it as my database.

I would really appreciate adices/ help/ messages/ :-) Thanks.

Answer 1

You don't need to switch to Jackson. Gson 2.1 introduced a new TypeAdapter interface that permits mixed tree and streaming serialization and deserialization.

The API is efficient and flexible. See Gson's Streaming doc for an example of combining tree and binding modes. This is strictly better than mixed streaming and tree modes; with binding you don't waste memory building an intermediate representation of your values.

Like Jackson, Gson has APIs to recursively skip an unwanted value; Gson calls this skipValue().

Answer 2

I will suggest to have a look at Jackson Api it is very easy to combine the streaming and tree-model parsing options: you can move through the file as a whole in a streaming way, and then read individual objects into a tree structure.

As an example, let's take the following input:

{    "records": [      {"field1": "aaaaa", "bbbb": "ccccc"},      {"field2": "aaa", "bbb": "ccc"}    ] ,   "special message": "hello, world!"  } 

Just imagine the fields being sparse or the records having a more complex structure.

The following snippet illustrates how this file can be read using a combination of stream and tree-model parsing. Each individual record is read in a tree structure, but the file is never read in its entirety into memory, making it possible to process JSON files gigabytes in size while using minimal memory.

import org.codehaus.jackson.map.*; import org.codehaus.jackson.*;  import java.io.File;  public class ParseJsonSample {     public static void main(String[] args) throws Exception {         JsonFactory f = new MappingJsonFactory();         JsonParser jp = f.createJsonParser(new File(args[0]));         JsonToken current;         current = jp.nextToken();         if (current != JsonToken.START_OBJECT) {             System.out.println("Error: root should be object: quiting.");             return;         }         while (jp.nextToken() != JsonToken.END_OBJECT) {             String fieldName = jp.getCurrentName();             // move from field name to field value             current = jp.nextToken();             if (fieldName.equals("records")) {                 if (current == JsonToken.START_ARRAY) {                     // For each of the records in the array                     while (jp.nextToken() != JsonToken.END_ARRAY) {                         // read the record into a tree model,                         // this moves the parsing position to the end of it                         JsonNode node = jp.readValueAsTree();                         // And now we have random access to everything in the object                         System.out.println("field1: " + node.get("field1").getValueAsText());                         System.out.println("field2: " + node.get("field2").getValueAsText());                     }                 } else {                     System.out.println("Error: records should be an array: skipping.");                     jp.skipChildren();                 }             } else {                 System.out.println("Unprocessed property: " + fieldName);                 jp.skipChildren();             }         }     } } 

As you can guess, the nextToken() call each time gives the next parsing event: start object, start field, start array, start object, ..., end object, ..., end array, ...

The jp.readValueAsTree() call allows to read what is at the current parsing position, a JSON object or array, into Jackson's generic JSON tree model. Once you have this, you can access the data randomly, regardless of the order in which things appear in the file (in the example field1 and field2 are not always in the same order). Jackson supports mapping onto your own Java objects too. The jp.skipChildren() is convenient: it allows to skip over a complete object tree or an array without having to run yourself over all the events contained in it.