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Remove Spark 1.x documentation from README; add links to older READMEs
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To avoid confusion, we should remove the documentation / linking instructions for the 2.x line of releases since the current README describes features which don't apply there. Instead, we should link to the older docs.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #199 from JoshRosen/readme-fixes.

(cherry picked from commit b01a034)
Signed-off-by: Josh Rosen <joshrosen@databricks.com>
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JoshRosen committed Nov 28, 2016
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34 changes: 7 additions & 27 deletions README.md
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Expand Up @@ -7,50 +7,31 @@ A library for reading and writing Avro data from [Spark SQL](http://spark.apache

## Requirements

This documentation is for Spark 1.4+ and 2.0.
This documentation is for version 3.1.0 of this library, which supports Spark 2.0+. For
documentation on earlier versions of this library, see the links below.

This library has different versions for Spark 1.2, 1.3, 1.4+, and 2.0:

| Spark Version | Compatible version of Avro Data Source for Spark |
| ------------- | ------------------------------------------------ |
| `1.2` | `0.2.0` |
| `1.3` | `1.0.0` |
| `1.4+` | `2.0.1` |
| `2.0` | `3.1.0` |
| `1.3` | [`1.0.0`](https://github.com/databricks/spark-avro/tree/v1.0.0) |
| `1.4+` | [`2.0.1`](https://github.com/databricks/spark-avro/tree/v2.0.1) |
| `2.0` | `3.1.0` (this version) |

## Linking

This library is cross-published for Scala 2.11, so 2.11 users should replace 2.10 with 2.11 in the commands listed below.

You can link against this library in your program at the following coordinates:

### For Spark 1.4+

Using SBT:

```
libraryDependencies += "com.databricks" %% "spark-avro" % "2.0.1"
```

Using Maven:

```xml
<dependency>
<groupId>com.databricks</groupId>
<artifactId>spark-avro_2.10</artifactId>
<version>2.0.1</version>
</dependency>
```

### For Spark 2.0

Using SBT:
**Using SBT:**

```
libraryDependencies += "com.databricks" %% "spark-avro" % "3.1.0"
```

Using Maven:
**Using Maven:**

```xml
<dependency>
Expand All @@ -66,7 +47,6 @@ This library can also be added to Spark jobs launched through `spark-shell` or `
For example, to include it when starting the spark shell:

```
$ bin/spark-shell --packages com.databricks:spark-avro_2.10:2.0.1
$ bin/spark-shell --packages com.databricks:spark-avro_2.11:3.1.0
```

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