fix broken links

docs/accuracy/definingOwn.md

@@ -5,7 +5,7 @@ description: To add blocking functions and how they work
 
 # Defining Own Functions
 
-You can add your own [blocking functions](https://github.com/zinggAI/zingg/tree/main/core/src/main/java/zingg/hash) which will be evaluated by Zingg to build the [blocking tree.](../zModels.md)
+You can add your own [blocking functions](https://github.com/zinggAI/zingg/tree/main/common/core/src/main/java/zingg/common/core/hash) which will be evaluated by Zingg to build the [blocking tree.](../zModels.md)
 
 The blocking tree works on the matched records provided by the user as part of the training. At every node, it selects the hash function and the field on which it should be applied so that there is the least elimination of the matching pairs. Say we have data like this:
 
@@ -49,8 +49,8 @@ Pair 1 is getting eliminated above, hence last1char is not a good function.&#x20
 
 So, first1char(firstname) will be chosen. This brings near similar records together - in a way, clusters them to break the cartesian join.
 
-These business-specific blocking functions go into [Hash Functions](https://github.com/zinggAI/zingg/tree/main/core/src/main/java/zingg/hash) and must be added to [HashFunctionRegistry](../../core/src/main/java/zingg/hash/HashFunctionRegistry.java) and [hash functions config](../../core/src/main/resources/hashFunctions.json).
+These business-specific blocking functions go into [Hash Functions](https://github.com/zinggAI/zingg/tree/main/common/core/src/main/java/zingg/common/core/hash) and must be added to [HashFunctionRegistry](https://github.com/zinggAI/zingg/blob/main/common/core/src/main/java/zingg/common/core/hash/HashFunctionRegistry.java) and [hash functions config](https://github.com/zinggAI/zingg/blob/main/common/core/src/main/resources/hashFunctions.json).
 
-Also, for similarity, you can define your own measures. Each dataType has predefined features, for example, [String](../../core/src/main/java/zingg/feature/StringFeature.java) fuzzy type is configured for Affine and Jaro.
+Also, for similarity, you can define your own measures. Each dataType has predefined features, for example, [String](https://github.com/zinggAI/zingg/blob/main/common/core/src/main/java/zingg/common/core/feature/StringFeature.java) fuzzy type is configured for Affine and Jaro.
 
-You can define your own [comparisons](https://github.com/zinggAI/zingg/tree/main/core/src/main/java/zingg/similarity/function) and use them.
+You can define your own [comparisons](https://github.com/zinggAI/zingg/tree/main/common/core/src/main/java/zingg/common/core/similarity/function) and use them.

docs/running/databricks.md

@@ -3,7 +3,7 @@ title: Running on Databricks
 parent: Running Zingg on Cloud
 nav_order: 6
 ---
-There are several ways to run Zingg on Databricks. All [file formats and data sources and sinks](../dataSourcesAndSinks) are supported within Databricks. 
+There are several ways to run Zingg on Databricks. All [file formats and data sources and sinks](https://github.com/zinggAI/zingg/tree/main/docs/dataSourcesAndSinks) are supported within Databricks. 
 
 # Running directly within Databricks using the Databricks notebook interface
 This uses the Zingg Python API and an [example notebook is available here](https://github.com/zinggAI/zingg/blob/main/examples/databricks/FebrlExample.ipynb)