"content_gl",
        "content_gu",
        "content_he",
        "content_hi",
        "content_hr",
        "content_hu",
        "content_hy",
        "content_id",
        "content_it",
        "content_ja",
        "content_ko",
        "content_lt",
        "content_lv",
        "content_mk",
        "content_ml",
        "content_nl",
        "content_no",

        "content_gl",
        "content_gu",
        "content_he",
        "content_hi",
        "content_hr",
        "content_hu",
        "content_hy",
        "content_id",
        "content_it",
        "content_ja",
        "content_ko",
        "content_lt",
        "content_lv",
        "content_mk",
        "content_ml",
        "content_nl",
        "content_no",

        assertEquals("aaa;ctx._source.title_ja=ctx._source.title;ctx._source.content_ja=ctx._source.content",
                languageHelper.createScript(doc, "aaa").getIdOrCode());
    }

    public void test_getReindexScriptSource() {
        assertEquals(
                "if(ctx._source.lang!=null){ctx._source['title_'+ctx._source.lang]=ctx._source.title;ctx._source['content_'+ctx._source.lang]=ctx._source.content}",

        assertEquals(threadCount * operationsPerThread, successCount.get());
        assertTrue(overallTimeMs < 1000, "Operations should complete quickly without lock contention");

        pool.close();
    }

    /**
     * Test buffer cache performance with concurrent operations
     */
    @Test
    public void testBufferCachePerformance() throws Exception {

  /**
   * Guides the allowed concurrency among update operations. Used as a hint for internal sizing. The
   * table is internally partitioned to try to permit the indicated number of concurrent updates
   * without contention. Because assignment of entries to these partitions is not necessarily
   * uniform, the actual concurrency observed may vary. Ideally, you should choose a value to

- Lease entries should be evicted based on LRU when max leases reached
- Implement periodic cleanup of expired leases

### 9.2 Thread Safety
- Use concurrent data structures for lease storage
- Minimize lock contention in hot paths
- Async handling of lease breaks

### 9.3 Network Efficiency
- Batch lease requests when possible
- Implement lease key reuse for related files
- Optimize lease break acknowledgment timing

 * <i>stripes</i>, increasing the granularity of a single lock and allowing independent operations
 * to lock different stripes and proceed concurrently, instead of creating contention for a single
 * lock.
 *
 * <p>The guarantee provided by this class is that equal keys lead to the same lock (or semaphore),
 * i.e. {@code if (key1.equals(key2))} then {@code striped.get(key1) == striped.get(key2)} (assuming

    Castle is great! But it's a large dependency (6.5 MiB) and its security provider feature
    impacts VM-wide behavior.

 *  New: Reduce contention for applications that make a very high number of concurrent requests.
    Previously OkHttp used its connection pool as a lock when making changes to connections and

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *