Apply a few more updates

tests/mgbench/README.md

@@ -96,7 +96,7 @@ Benchmarking different systems is challenging because the setup, environment, qu
 Listed below are the main scripts used to run the benchmarks:
 
 - `benchmark.py` - The main entry point used for starting and managing the execution of the benchmark. This script initializes all the necessary files, classes, and objects. It starts the database and the benchmark and gathers the results.
-- `base.py` - This is the base workload class. All other workloads are subclasses located in the workloads directory. For example, ldbc_interactive.py defines ldbc interactive dataset and queries (but this is NOT an official LDBC interactive workload). Each workload class can generate the dataset, use custom import ofthe dataset or provide a CYPHERL file for the import process..
+- `base.py` - This is the base workload class. All other workloads are subclasses located in the workloads directory. For example, ldbc_interactive.py defines ldbc interactive dataset and queries (but this is NOT an official LDBC interactive workload). Each workload class can generate the dataset, use custom import of the dataset or provide a CYPHERL file for the import process..
 - `runners.py` - The script that configures, starts, and stops the database.
 - `client.cpp` - Client for querying the database.
 - `graph_bench.py` - Script that starts all tests from Benchgraph.

tests/mgbench/benchmark.py

@@ -239,7 +239,11 @@ def sanitize_args(args):
     assert args.benchmarks != None, helpers.list_available_workloads()
     assert args.num_workers_for_import > 0
     assert args.num_workers_for_benchmark > 0
-    assert args.export_results != None, "Pass where will results be saved"
+    assert (
+        args.export_results != None
+        or args.export_results_on_disk_txn != None
+        or args.export_results_in_memory_analytical != None
+    ), "Pass where will results be saved"
     assert args.single_threaded_runtime_sec >= 1, "Low runtime value, consider extending time for more accurate results"
     assert (
         args.workload_realistic == None or args.workload_mixed == None
@@ -686,25 +690,25 @@ def run_target_workload(benchmark_context, workload, bench_queries, vendor_runne
             run_isolated_workload_with_authorization(vendor_runner, client, bench_queries, group, workload, results)
 
 
-# TODO: (andi) Reorder functions in top-down notion in order to improve readibility
+# TODO: (andi) Reorder functions in top-down notion in order to improve readibility -> does this referes to run_target_workloads function or the code around?
 def run_target_workloads(benchmark_context, target_workloads, bench_results):
     for workload, bench_queries in target_workloads:
         log.info(f"Started running {str(workload.NAME)} workload")
-
         benchmark_context.set_active_workload(workload.NAME)
         benchmark_context.set_active_variant(workload.get_variant())
 
+        # TODO(gitbuda): What's the semantic of --export-results-xyz flags? NOTE: avoid nested if/else statements
         if workload.is_disk_workload() and benchmark_context.export_results_on_disk_txn:
             run_on_disk_transactional_benchmark(benchmark_context, workload, bench_queries, bench_results.disk_results)
-        else:
-            run_in_memory_transactional_benchmark(
-                benchmark_context, workload, bench_queries, bench_results.in_memory_txn_results
+            return
+        if benchmark_context.export_results_in_memory_analytical:
+            run_in_memory_analytical_benchmark(
+                benchmark_context, workload, bench_queries, bench_results.in_memory_analytical_results
             )
-
-            if benchmark_context.export_results_in_memory_analytical:
-                run_in_memory_analytical_benchmark(
-                    benchmark_context, workload, bench_queries, bench_results.in_memory_analytical_results
-                )
+            return
+        run_in_memory_transactional_benchmark(
+            benchmark_context, workload, bench_queries, bench_results.in_memory_txn_results
+        )
 
 
 def run_on_disk_transactional_benchmark(benchmark_context, workload, bench_queries, disk_results):

tests/mgbench/runners.py

@@ -811,7 +811,7 @@ class MemgraphDocker(BaseRunner):
                 "-it",
                 "-p",
                 self._bolt_port + ":" + self._bolt_port,
-                "memgraph/memgraph:2.13.0", # TODO(gitbuda): parametrize & fallback to the latest version.
+                "memgraph/memgraph:2.14.0",  # TODO(gitbuda): parametrize & fallback to the latest version.
                 "--storage_wal_enabled=false",
                 "--storage_recover_on_startup=true",
                 "--storage_snapshot_interval_sec",