Fixed config for experiment depth queries

README.md

@@ -39,13 +39,13 @@ In this project, I compute the PageRanks for all packages from 15 package manage
 
 # Results
 
-The results of computation of PageRanks and truck factors -incorporating the results of computing criticality with the current _criticality_score_- can be found in [./data/output/comparison.csv](./data/output/comparison.csv)). The top 1000 ranked projects per package manager can be found under [./data/output/](./data/output/)), where the file names are `<pkg_manager>_top_1000.csv`.
+The results of computation of PageRanks and truck factors -incorporating the results of computing criticality with the current _criticality_score_- can be found in [./data/output/comparison.adoc](./data/output/comparison.adoc)). The top 1000 ranked projects per package manager can be found under [./data/output/](./data/output/)), where the file names are `<pkg_manager>_top_1000.csv`.
 
 In the following some examples from the results:
 <!-- 
 ## Python Projects from PyPI
  -->
-On PyPI, there are in total 231690 packages of which 182498 (ca. 79%) have do neither depend on another package nor are dependent of another package, i.e., in- and out-degree of the package is equal to zero. Of the remaining 49192 packages, 17680 have either a direct dependency (only 424) or a transitive dependency ending on `idna`. That is, around a third (36%) of the packages that are connected in the dependency graph require either directly or indirectly the project `idna`. However, the `criticality_score` in its current configuration is only 0.41, whereas the pagerank of it is 109.91, which is the 14th highest in the PyPI dependency graph. Consequently, the `criticality_score` would suggest that the `idna` project is not particularly important. In reality it is, since -next to having so many projects depending on it- it is even discussed to [merge it into the standard library](https://github.com/kjd/idna/issues/67). `idna` is also _critical_ since it is mainly maintained by a single person. The project's truck factor is one. Even though there are currently 11 contributors, [Kim Davies](https://github.com/kjd) accounts for ca. 2/3 of all commits (67%) changing the absolute majority of code in the project.
+On PyPI, there are in total 231690 packages of which 182498 (ca. 79%)  do neither depend on another package nor are dependent of another package, i.e., in- and out-degree of the package is equal to zero. Of the remaining 49192 packages, 17680 have either a direct dependency (only 424) or a transitive dependency ending on `idna`. That is, around a third (36%) of the packages that are connected in the dependency graph require either directly or indirectly the project `idna`. However, the `criticality_score` in its current configuration is only 0.41, whereas the pagerank of it is 109.91, which is the 14th highest in the PyPI dependency graph. Consequently, the `criticality_score` would suggest that the `idna` project is not particularly important. In reality it is, since -next to having so many projects depending on it- it is even discussed to [merge it into the standard library](https://github.com/kjd/idna/issues/67). `idna` is also _critical_ since it is mainly maintained by a single person. The project's truck factor is one. Even though there are currently 11 contributors, [Kim Davies](https://github.com/kjd) accounts for ca. 2/3 of all commits (67%) changing the absolute majority of code in the project.
 
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create_db.sh

@@ -55,8 +55,8 @@ docker run \
     -v $(pwd)/neo4j/logs:/logs \
     -v $(pwd)/data/processing:/var/lib/neo4j/import \
     -v $(pwd)/neo4j/plugins:/plugins \
-    --env NEO4J_dbms_memory_heap_initial__size=1G \
-    --env NEO4J_dbms_memory_heap_max__size=1G \
+    --env NEO4J_dbms_memory_heap_initial__size=4G \
+    --env NEO4J_dbms_memory_heap_max__size=4G \
     --env NEO4J_dbms_security_procedures_unrestricted=gds.\\\* \
     --env NEO4J_AUTH=neo4j/password \
     neo4j:4.2