java 46 lines · 8 steps

Rebuilding a search index at Spring startup

An ApplicationRunner streams every active product and writes it into a search view in fixed-size batches when the app boots.

Explained by highlit
Spring Intermediate startup-hook batching streaming search-index dependency-injection
1@Component
2@Order(20)
3public class ProductSearchIndexRunner implements ApplicationRunner {
4 
5 private static final Logger log = LoggerFactory.getLogger(ProductSearchIndexRunner.class);
6 
7 private final ProductRepository products;
8 private final ProductSearchView searchView;
9 
10 public ProductSearchIndexRunner(ProductRepository products, ProductSearchView searchView) {
11 this.products = products;
12 this.searchView = searchView;
13 }
14 
15 @Override
16 public void run(ApplicationArguments args) {
17 if (args.containsOption("skip-index")) {
18 log.info("Skipping product search index rebuild (--skip-index present)");
19 return;
20 }
21 
22 StopWatch watch = new StopWatch();
23 watch.start();
24 searchView.clear();
25 
26 int indexed = 0;
27 try (Stream<Product> stream = products.streamAllActive()) {
28 List<ProductDocument> batch = new ArrayList<>(500);
29 for (Product product : (Iterable<Product>) stream::iterator) {
30 batch.add(ProductDocument.from(product));
31 if (batch.size() == 500) {
32 searchView.saveAll(batch);
33 indexed += batch.size();
34 batch.clear();
35 }
36 }
37 if (!batch.isEmpty()) {
38 searchView.saveAll(batch);
39 indexed += batch.size();
40 }
41 }
42 
43 watch.stop();
44 log.info("Rebuilt product search index: {} documents in {} ms", indexed, watch.getTotalTimeMillis());
45 }
46}
01 / 01
STEP 01

Walkthrough

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Three takeaways
  1. 1ApplicationRunner lets you run one-off work after the context is ready, ordered against other runners.
  2. 2Streaming rows and flushing in fixed-size batches keeps memory flat over large datasets.
  3. 3A command-line flag gives operators an escape hatch to skip expensive startup work.

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