"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.
   *

As an alpha feature, Kubernetes v1.22 can use the cgroups v2 API to control memory allocation and isolation. This feature is designed to improve workload and node availability when there is contention for memory resources.

### API changes and improvements for ephemeral containers